Data engineer jobs in Teaneck, NJ

DL Software produces Godel, a financial information and trading terminal. Role Description This is a full-time, on-site role based in New York, NY, for a Data Engineer. The Data Engineer will design, build, and maintain scalable data systems and pipelines. Responsibilities include data modeling, developing and managing ETL workflows, optimizing data storage solutions, and supporting data warehousing initiatives. The role also involves collaborating with cross-functional teams to improve data accessibility and analytics capabilities. Qualifications Strong proficiency in Data Engineering and Data Modeling Mandatory: strong experience in global financial instruments including equities, fixed income, options and exotic asset classes Strong Python background Expertise in Extract, Transform, Load (ETL) processes and tools Experience in designing, managing, and optimizing Data Warehousing solutions

NYC NY / Hybrid 12+ Months Project - Leveraging Llama to extract cybersecurity insights out of unstructured data from their ticketing system. Must have strong experience with: Llama Python Hadoop MCP Machine Learning (ML) They need a strong developer - using llama and Hadoop (this is where the data sits), experience with MCP. They have various ways to pull the data out of their tickets but want someone who can come in and make recommendations on the best way to do it and then get it done. They have tight timelines. Thanks and Regards! Lavkesh Dwivedi ************************ Amtex System Inc. 28 Liberty Street, 6th Floor | New York, NY - 10005 ************ ********************

The Senior Data Analyst will be responsible for developing MS SQL queries and procedures, building custom reports, and modifying ERP user forms to support and enhance organizational productivity. This role will also design and maintain databases, ensuring high levels of stability, reliability, and performance. Responsibilities Analyze, structure, and interpret raw data. Build and maintain datasets for business use. Design and optimize database tables, schemas, and data structures. Enhance data accuracy, consistency, and overall efficiency. Develop views, functions, and stored procedures. Write efficient SQL queries to support application integration. Create database triggers to support automation processes. Oversee data quality, integrity, and database security. Translate complex data into clear, actionable insights. Collaborate with cross-functional teams on multiple projects. Present data through graphs, infographics, dashboards, and other visualization methods. Define and track KPIs to measure the impact of business decisions. Prepare reports and presentations for management based on analytical findings. Conduct daily system maintenance and troubleshoot issues across all platforms. Perform additional ad hoc analysis and tasks as needed. Qualification Bachelor's Degree in Information Technology or relevant 4+ years of experience as a Data Analyst or Data Engineer, including database design experience. Strong ability to extract, manipulate, analyze, and report on data, as well as develop clear and effective presentations. Proficiency in writing complex SQL queries, including table joins, data aggregation (SUM, AVG, COUNT), and creating, retrieving, and updating views. Excellent written, verbal, and interpersonal communication skills. Ability to manage multiple tasks in a fast-paced and evolving environment. Strong work ethic, professionalism, and integrity. Advanced proficiency in Microsoft Office applications.

Senior Data Engineer (Snowflake & Python) 1-Year Contract | $60/hour + Benefit Options Hybrid: On-site a few days per month (local candidates only) Work Authorization Requirement You must be authorized to work for any employer as a W2 employee. This is required for this role. This position is W-2 only - no C2C, no third-party submissions, and no sponsorship will be considered. Overview We are seeking a Senior Data Engineer to support enterprise-scale data initiatives for a highly collaborative engineering organization. This is a new, long-term contract opportunity for a hands-on data professional who thrives in fast-paced environments and enjoys building high-quality, scalable data solutions on Snowflake. Candidates must be based in or around New Jersey, able to work on-site at least 3 days per month, and meet the W2 employment requirement. What You'll Do Design, develop, and support enterprise-level data solutions with a strong focus on Snowflake Participate across the full software development lifecycle - planning, requirements, development, testing, and QA Partner closely with engineering and data teams to identify and implement optimal technical solutions Build and maintain high-performance, scalable data pipelines and data warehouse architectures Ensure platform performance, reliability, and uptime, maintaining strong coding and design standards Troubleshoot production issues, identify root causes, implement fixes, and document preventive solutions Manage deliverables and priorities effectively in a fast-moving environment Contribute to data governance practices including metadata management and data lineage Support analytics and reporting use cases leveraging advanced SQL and analytical functions Required Skills & Experience 8+ years of experience designing and developing data solutions in an enterprise environment 5+ years of hands-on Snowflake experience Strong hands-on development skills with SQL and Python Proven experience designing and developing data warehouses in Snowflake Ability to diagnose, optimize, and tune SQL queries Experience with Azure data frameworks (e.g., Azure Data Factory) Strong experience with orchestration tools such as Airflow, Informatica, Automic, or similar Solid understanding of metadata management and data lineage Hands-on experience with SQL analytical functions Working knowledge of Shell scripting and Java scripting Experience using Git, Confluence, and Jira Strong problem-solving and troubleshooting skills Collaborative mindset with excellent communication skills Nice to Have Experience supporting Pharma industry data Exposure to Omni-channel data environments Why This Opportunity $60/hour W2 on a long-term 1-year contract Benefit options available Hybrid structure with limited on-site requirement High-impact role supporting enterprise data initiatives Clear expectations: W-2 only, no third-party submissions, no Corp-to-Corp This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

***This role is hybrid three days per week onsite in Parsippany, NJ. LOCAL CANDIDATES ONLY. No relocation*** Data Scientist • Summary: Provide analytics, telemetry, ML/GenAI-driven insights to measure SDLC health, prioritize improvements, validate pilot outcomes, and implement AI-driven development lifecycle capabilities. • Responsibilities: o Define metrics and instrumentation for SDLC/CI pipelines, incidents, and delivery KPIs. o Build dashboards, anomaly detection, and data models; implement GenAI solutions (e.g., code suggestion, PR summarization, automated test generation) to improve developer workflows. o Design experiments and validate AI-driven features during the pilot. o Collaborate with engineering and SRE to operationalize models and ensure observability and data governance. • Required skills: o 3+ years applied data science/ML in production; hands-on experience with GenAI/LLMs applied to developer workflows or DevOps automation. o Strong Python (pandas, scikit-learn), ML frameworks, SQL, and data visualization (Tableau/Power BI). o Experience with observability/telemetry data (logs/metrics/traces) and A/B experiment design. • Preferred: o Experience with model deployment, MLOps, prompt engineering, and cloud data platforms (AWS/GCP/Azure).

Apexon is a digital-first technology services firm specializing in accelerating business transformation and delivering human-centric digital experiences. We have been meeting customers wherever they are in the digital lifecycle and helping them outperform their competition through speed and innovation.Apexon brings together distinct core competencies - in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences - to help businesses capitalize on the unlimited opportunities digital offers. Our reputation is built on a comprehensive suite of engineering services, a dedication to solving clients' toughest technology problems, and a commitment to continuous improvement. Backed by Goldman Sachs Asset Management and Everstone Capital, Apexon now has a global presence of 15 offices (and 10 delivery centers) across four continents. Job Description Experienced Data management specialist responsible for developing, overseeing, organizing, storing, and analyzing data and data systems Participate in all aspects of the software development lifecycle for Snowflake solutions, including planning, requirements, development, testing, and quality assurance Work in tandem with our engineering team to identify and implement the most optimal solutions Ensure platform performance, uptime, and scale, maintaining high standards for code quality and thoughtful design Troubleshoot incidents, identify root causes, fix and document problems, and implement preventive measures Able to manage deliverables in fast paced environments Areas of Expertise At least 10 years of experience designing and development of data solutions in enterprise environment At least 5+ years' experience on Snowflake Platform Strong hands-on SQL and Python development Experience with designing and developing data warehouses in Snowflake A minimum of three years' experience in developing production-ready data ingestion and processing pipelines using Spark, Scala Strong hands-on experience with Orchestration Tools e.g. Airflow, Informatica, Automic Good understanding on Metadata and data lineage Hands-on knowledge on SQL Analytical functions Strong knowledge and hands-on experience in Shell scripting, Java Scripting Able to demonstrate experience with software engineering practices including CI/CD, Automated testing and Performance Engineering. Good understanding and exposure to Git, Confluence and Jira Good problem solving and troubleshooting skills. Team player, collaborative approach and excellent communication skills Our Commitment to Diversity & Inclusion: Did you know that Apexon has been Certified™ by Great Place To Work , the global authority on workplace culture, in each of the three regions in which it operates: USA (for the fourth time in 2023), India (seven consecutive certifications as of 2023), and the UK.Apexon is committed to being an equal opportunity employer and promoting diversity in the workplace. We are taking affirmative action to ensure equal employment opportunity for all qualified individuals. Apexon strictly prohibits discrimination and harassment of any kind and provides equal employment opportunities to employees and applicants without regard to gender, race, color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. You can read about our Job Applicant Privacy policy here Job Applicant Privacy Policy (apexon.com)

Are you a data engineer who loves building systems that power real impact in the world? A fast growing healthcare technology organization is expanding its innovation team and is looking for a Data Engineer II to help build the next generation of its data platform. This team sits at the center of a major transformation effort, partnering closely with engineering, analytics, and product to design the foundation that supports advanced automation, AI, intelligent workflows, and high scale data operations that drive measurable outcomes for hospitals, health systems, and medical groups. In this role, you will design, develop, and maintain software applications that process large volumes of data every day. You will collaborate with cross functional teams to understand data requirements, build and optimize data models, and create systems that ensure accuracy, reliability, and performance. You will write code that extracts, transforms, and loads data from a variety of sources into modern data warehouses and data lakes, while implementing best in class data quality and governance practices. You will work hands on with big data technologies such as Hadoop, Spark, and Kafka, and you will play a critical role in troubleshooting, performance tuning, and ensuring the scalability of complex data applications. To thrive here, you should bring strong problem solving ability, analytical thinking, and excellent communication skills. This is an opportunity to join an expanding innovation group within a leading healthcare platform that is investing heavily in data, AI, and the future of intelligent revenue operations. If you want to build systems that make a real difference and work with teams that care deeply about improving patient experiences and provider performance, this is a chance to do highly meaningful engineering at scale.

Title: Data Engineer (Web Scraping technologies) Duration: FTE/Perm Salary: 125-190k plus bonus Responsibilities: Utilize AI Models, Code, Libraries or applications to enable a scalable Web Scraping capability Web Scraping Request Management including intake, assessment, accessing sites to scrape, utilizing tools to scrape, storage of scrape, validation and entitlement to users Fielding Questions from users about the scrapes and websites Coordinating with Compliance on approvals and TOU reviews Some Experience building Data pipelines in AWS platform utilizing existing tools like Cron, Glue, Eventbridge, Python based ETL, AWS Redshift Normalizing/standardizing vendor data, firm data for firm consumption Implement data quality checks to ensure reliability and accuracy of scraped data Coordinate with Internal teams on delivery, access, requests, support Promote Data Engineering best practices Required Skills and Qualifications: Bachelor's degree in computer science, Engineering, Mathematics or related field 2-5 experience in a similar role Prior buy side experience is strongly preferred (Multi-Strat/Hedge Funds) Capital markets experience is necessary with good working knowledge of reference data across asset classes and experience with trading systems AWS cloud experience with commons services (S3, lambda, cron, Event Bridge etc.) Experience with web-scraping frameworks (Scrapy, BeautifulSoup, Selenium, Playwright etc.) Strong hands-on skills with NoSQL and SQL databases, programming in Python, data pipeline orchestration tools and analytics tools Familiarity with time series data and common market data sources (Bloomberg, Refinitiv etc.) Familiarity with modern Dev Ops practices and infrastructure-as-code tools (e.g. Terraform, CloudFormation) Strong communication skills to work with stakeholders across technology, investment, and operations teams.

· Expert level skills writing and optimizing complex SQL · Experience with complex data modelling, ETL design, and using large databases in a business environment · Experience with building data pipelines and applications to stream and process datasets at low latencies · Fluent with Big Data technologies like Spark, Kafka and Hive · Expert level understanding on Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service is required · Designing and building of data pipelines using API ingestion and Streaming ingestion methods · Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is essential · Experience in developing NO SQL solutions using Azure Cosmos DB is essential · Thorough understanding of Azure and AWS Cloud Infrastructure offerings · Working knowledge of Python is desirable · Designing and implementing scalable and secure data processing pipelines using Azure Data Factory, Azure Databricks, and other Azure services · Managing and optimizing data storage using Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Cosmos DB · Monitoring and troubleshooting data-related issues within the Azure environment to maintain high availability and performance · Implementing data security measures, including encryption, access controls, and auditing, to protect sensitive information · Automating data pipelines and workflows to streamline data ingestion, processing, and distribution tasks · Utilizing Azure's analytics services, such as Azure Synapse Analytics, to provide insights and support data-driven decision-making. · Documenting data procedures, systems, and architectures to maintain clarity and ensure compliance with regulatory standards · Providing guidance and support for data governance, including metadata management, data lineage, and data cataloging Best Regards, Dipendra Gupta Technical Recruiter *****************************

We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron's progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,500+, and has 58 offices in 21 countries within key global markets. Our challenge We are looking for a candidate will be responsible for designing, implementing, and managing data solutions on the Azure platform in Financial / Banking domain. Additional Information* The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within New York City, NY is $130k - $140k/year & benefits (see below). The Role Responsibilities: Lead the development and optimization of batch and real-time data pipelines, ensuring scalability, reliability, and performance. Architect, design, and deploy data integration, streaming, and analytics solutions leveraging Spark, Kafka, and Snowflake. Ability to help voluntarily and proactively, and support Team Members, Peers to deliver their tasks to ensure End-to-end delivery. Evaluates technical performance challenges and recommend tuning solutions. Hands-on knowledge of Data Service Engineer to design, develop, and maintain our Reference Data System utilizing modern data technologies including Kafka, Snowflake, and Python. Requirements: Proven experience in building and maintaining data pipelines, especially using Kafka, Snowflake, and Python. Strong expertise in distributed data processing and streaming architectures. Experience with Snowflake data warehouse platform: data loading, performance tuning, and management. Proficiency in Python scripting and programming for data manipulation and automation. Familiarity with Kafka ecosystem (Confluent, Kafka Connect, Kafka Streams). Knowledge of SQL, data modelling, and ETL/ELT processes. Understanding of cloud platforms (AWS, Azure, GCP) is a plus. Domain Knowledge in any of the below area: Trade Processing, Settlement, Reconciliation, and related back/middle-office functions within financial markets (Equities, Fixed Income, Derivatives, FX, etc.). Strong understanding of trade lifecycle events, order types, allocation rules, and settlement processes. Funding Support, Planning & Analysis, Regulatory reporting & Compliance. Knowledge of regulatory standards (such as Dodd-Frank, EMIR, MiFID II) related to trade reporting and lifecycle management. We offer: A highly competitive compensation and benefits package. A multinational organization with 58 offices in 21 countries and the possibility to work abroad. 10 days of paid annual leave (plus sick leave and national holidays). Maternity & paternity leave plans. A comprehensive insurance plan including medical, dental, vision, life insurance, and long-/short-term disability (plans vary by region). Retirement savings plans. A higher education certification policy. Commuter benefits (varies by region). Extensive training opportunities, focused on skills, substantive knowledge, and personal development. On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses. Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups. Cutting edge projects at the world's leading tier-one banks, financial institutions and insurance firms. A flat and approachable organization. A truly diverse, fun-loving, and global work culture. S YNECHRON'S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference' is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Title: Senior Azure Data Engineer Client: Major Japanese Bank Experience Level: Senior (10+ Years) The Senior Azure Data Engineer will design, build, and optimize enterprise data solutions within Microsoft Azure for a major Japanese bank. This role focuses on architecting scalable data pipelines, enhancing data lake environments, and ensuring security, compliance, and data governance best practices. Key Responsibilities: Develop, maintain, and optimize Azure-based data pipelines and ETL/ELT workflows. Design and implement Azure Data Lake, Synapse, Databricks, and ADF solutions. Ensure data security, compliance, lineage, and governance controls. Partner with architecture, data governance, and business teams to deliver high-quality data solutions. Troubleshoot performance issues and improve system efficiency. Required Skills: 10+ years of data engineering experience. Strong hands-on expertise with Azure Synapse, Azure Data Factory, Azure Databricks, Azure Data Lake, and Azure SQL. Azure certifications strongly preferred. Strong SQL, Python, and cloud data architecture skills. Experience in financial services or large enterprise environments preferred.

Immediate need for a talented Data Architect. This is a 12 month contract opportunity with long-term potential and is located in Basking Ridge, NJ (Hybrid). Please review the job description below and contact me ASAP if you are interested. Job ID:25-93859 Pay Range: $110 - $120/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location). Key Requirements and Technology Experience: Key Skills; ETL, LTMC, SaaS . 5 years as a Data Architect 5 years in ETL 3 years in LTMC Our client is a leading Telecom Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration. Pyramid Consulting, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, colour, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. By applying to our jobs you agree to receive calls, AI-generated calls, text messages, or emails from Pyramid Consulting, Inc. and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here.

LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 750 clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by nearly 90,000 talented and entrepreneurial professionals across more than 30 countries, LTIMindtree - a Larsen & Toubro Group company - combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale. For more information, please visit ******************* Job Title: Principal Data Modeler / Data Architecture Lead - Capital Markets Work Location Jersey City, NJ (Onsite, 5 days / week) Job Description: We are seeking a highly experienced Principal Data Modeler / Data Architecture Lead to reverse engineer an existing logical data model supporting all major lines of business in the capital markets domain. The ideal candidate will have deep capital markets domain expertise and will work closely with business and technology stakeholders to elicit and document requirements, map those requirements to the data model, and drive enhancements or rationalization of the logical model prior to its conversion to a physical data model. A software development background is not required. Key Responsibilities Reverse engineers the current logical data model, analyzing entities, relationships, and subject areas across capital markets (including customer, account, portfolio, instruments, trades, settlement, funds, reporting, and analytics). Engage with stakeholders (business, operations, risk, finance, compliance, technology) to capture and document business and functional requirements, and map these to the data model. Enhance or streamline the logical data model, ensuring it is fit-for-purpose, scalable, and aligned with business needs before conversion to a physical model. Lead the logical-to-physical data model transformation, including schema design, indexing, and optimization for performance and data quality. Perform advanced data analysis using SQL or other data analysis tools to validate model assumptions, support business decisions, and ensure data integrity. Document all aspects of the data model, including entity and attribute definitions, ERDs, source-to-target mappings, and data lineage. Mentor and guide junior data modelers, providing coaching, peer reviews, and best practices for modeling and documentation. Champion a detail-oriented and documentation-first culture within the data modeling team. Qualifications Minimum 15 years of experience in data modeling, data architecture, or related roles within capital markets or financial services. Strong domain expertise in capital markets (e.g., trading, settlement, reference data, funds, private investments, reporting, analytics). Proven expertise in reverse engineering complex logical data models and translating business requirements into robust data architectures. Strong skills in data analysis using SQL and/or other data analysis tools. Demonstrated ability to engage with stakeholders, elicit requirements, and produce high-quality documentation. Experience in enhancing, rationalizing, and optimizing logical data models prior to physical implementation. Ability to mentor and lead junior team members in data modeling best practices. Passion for detail, documentation, and continuous improvement. Software development background is not required. Preferred Skills Experience with data modeling tools (e.g., ER/Studio, ERwin, Power Designer). Familiarity with capital markets, business processes and data flows. Knowledge of regulatory and compliance requirements in financial data management. Exposure to modern data platforms (e.g., Snowflake, Databricks, cloud databases). Benefits and Perks: Comprehensive Medical Plan Covering Medical, Dental, Vision Short Term and Long-Term Disability Coverage 401(k) Plan with Company match Life Insurance Vacation Time, Sick Leave, Paid Holidays Paid Paternity and Maternity Leave LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, colour, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.

NeenOpal is a global consulting firm specializing in Data Science and Business Intelligence, with offices in Bengaluru, Newark, and Fredericton. We provide end-to-end solutions tailored to the unique needs of businesses, from startups to large organizations, across domains like digital strategy, sales and marketing, supply chain, and finance. Our mission is to help organizations achieve operational excellence and transform into data-driven enterprises. Role Description This is a full-time, hybrid, Data Engineer role located in Newark, NJ. The Data Engineer will be responsible for designing, implementing, and managing data engineering solutions to support business needs. Day-to-day tasks include building and optimizing data pipelines, developing and maintaining data models and ETL processes, managing data warehousing solutions, and contributing to the organization's data analytics initiatives. Collaboration with cross-functional teams to ensure robust data infrastructure will be a key aspect of this role. Key Responsibilities Data Pipeline Development: Design, implement, and manage robust data pipelines to ensure efficient data flow into data warehouses. Automate ETL processes using Python and advanced data engineering tools. Data Integration: Integrate and transform data using industry-standard tools. Experience required with: AWS Services: AWS Glue, Data Pipeline, Redshift, and S3. Azure Services: Azure Data Factory, Synapse Analytics, and Blob Storage. Data Warehousing: Implement and optimize solutions using Snowflake and Amazon Redshift. Database Management: Develop and manage relational databases (SQL Server, MySQL, PostgreSQL) to ensure data integrity. Performance Optimization: Continuously monitor and improve data processing workflows and apply best practices for query optimization. Global Collaboration: Work closely with cross-functional teams in the US, India, and Canada to deliver high-quality solutions. Governance & Support: Document ETL processes and data mappings in line with governance standards. Diagnose and resolve data-related issues promptly. Required Skills and Experience Experience: Minimum 2+ years of experience designing and developing ETL processes (AWS Glue, Azure Data Factory, or similar). Integration: Experience integrating data via RESTful / GraphQL APIs. Programming: Proficient in Python for ETL automation and SQL for database management. Cloud Platforms: Strong experience with AWS or Azure data services. (GCP familiarity is a plus) . Data Warehousing: Expertise with Snowflake, Amazon Redshift, or Azure Synapse Analytics. Integration: Experience integrating data via RESTful APIs. Communication: Excellent articulation skills to explain technical work directly to clients and stakeholders. Authorization: Must have valid work authorization in the United States. Salary Range: $65,000- $80,000 per year Benefits: This role includes health insurance, paid time off, and opportunities for professional growth and continuous learning within a fast-growing global analytics company. Equal Opportunity Employer NeenOpal Inc. is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

The Scientific Computing and Data group at the Icahn School of Medicine at Mount Sinai partners with scientists to accelerate scientific discovery. To achieve these aims, we support a cutting-edge high-performance computing and data ecosystem along with MD/PhD-level support for researchers. The group is composed of a high-performance computing team, a clinical data warehouse team and a data services team. The Lead HPC Architect, Cybersecurity, High Performance Computational and Data Ecosystem, is responsible for designing, implementing, and managing the cybersecurity infrastructure and technical operations of Scientific Computing's computational and data science ecosystem. This ecosystem includes a 25,000+ core and 40+ petabyte usable high-performance computing (HPC) systems, clinical research databases, and a software development infrastructure for local and national projects. The HPC system is the fastest in the world at any academic biomedical center (Top 500 list). To meet Sinai's scientific and clinical goals, the Lead brings a strategic, tactical and customer-focused vision to evolve the ecosystem to be continually more resilient, secure, scalable and productive for basic and translational biomedical research. The Lead combines deep technical expertise in cybersecurity, HPC systems, storage, networking, and software infrastructure with a strong focus on service, collaboration, and strategic planning for researchers and clinicians throughout the organization and beyond. The Lead is an expert troubleshooter, productive partner and leader of projects. The lead will work with stakeholders to make sure the HPC infrastructure is in compliance with governmental funding agency requirements and to promote efficient resource utilizations for researchers This position reports to the Director for HPC and Data Ecosystem in Scientific Computing and Data. Key Responsibilities: HPC Cybersecurity & System Administration: Design, implement, and manage all cybersecurity operations within the HPC environment, ensuring alignment with industry standards (NIST, ISO, GDPR, HIPAA, CMMC, NYC Cyber Command, etc.). Implement best practices for data security, including but not limited to encryption (at rest, in transit, and in use), audit logging, access control, authentication control, configuration managements, secure enclaves, and confidential computing. Perform full-spectrum HPC system administration: installation, monitoring, maintenance, usage reporting, troubleshooting, backup and performance tuning across HPC applications, web service, database, job scheduler, networking, storage, computes, and hardware to optimize workload efficiency. Lead resolution of complex cybersecurity and system issues; provide mentorship and technical guidance to team members. Ensure that all designs and implementations meet cybersecurity, performance, scalability, and reliability goals. Ensure that the design and operation of the HPC ecosystem is productive for research. Lead the integration of HPC resources with laboratory equipment for data ingestion aligned with all regulatory such as genomic sequencers, microscopy, clinical system etc. Develop, review and maintain security policies, risk assessments, and compliance documentation accurately and efficiently. Collaborate with institutional IT, compliance, and research teams to ensure all regulatory, Sinai Policy and operational alignment. Design and implement hybrid and cloud-integrated HPC solutions using on-premise and public cloud resources. Partner with other peers regionally, nationally and internationally to discover, propose and deploy a world-class research infrastructure for Mount Sinai. Stay current with emerging HPC, cloud, and cybersecurity technologies to keep the organization's infrastructure up-to-date. Work collaboratively, effectively and productively with other team members within the group and across Mount Sinai. Provide after-hours support as needed. Perform other duties as assigned or requested. Requirements: Bachelor's degree in computer science, engineering or another scientific field. Master's or PhD preferred. 10 years of progressive HPC system administration experience with Enterprise Linux releases including RedHat/CentOS/Rocky Systems, and batch cluster environment. Experience with all aspects of high-throughput HPC including schedulers (LSF or Slurm), networking (Infiniband/Gigabit Ethernet), parallel file systems and storage, configuration management systems (xCAT, Puppet and/or Ansible), etc. Proficient in cybersecurity processes, posture, regulations, approaches, protocols, firewalls, data protection in a regulated environment (e.g. finance, healthcare). In-depth knowledge HIPAA, NIST, FISMA, GDPR and related compliance standards, with prove experience building and maintaining compliant HPC system Experience with secure enclaves and confidential computing. Proven ability to provide mentorship and technical leadership to team members. Proven ability to lead complex projects to completion in collaborative, interdisciplinary settings with minimum guidance. Excellent analytical ability and troubleshooting skills. Excellent communication, documentation, collaboration and interpersonal skills. Must be a team player and customer focused. Scripting and programming experience. Preferred Experience Proficient with cloud services, orchestration tools, openshift/Kubernetes cost optimization and hybrid HPC architectures. Experience with Azure, AWS or Google cloud services. Experience with LSF job scheduler and GPFS Spectrum Scale. Experience in a healthcare environment. Experience in a research environment is highly preferred. Experience with software that enables privacy-preserving linking of PHI. Experience with Globus data transfer. Experience with Web service, SAP HANA, Oracle, SQL, MariaDB and other database technologies. Strength through Unity and Inclusion The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai's unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual. At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history. About the Mount Sinai Health System: Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time - discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients' medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status. Equal Opportunity Employer The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

Haptiq is a leader in AI-powered enterprise operations, delivering digital solutions and consulting services that drive value and transform businesses. We specialize in using advanced technology to streamline operations, improve efficiency, and unlock new revenue opportunities, particularly within the private capital markets. Our integrated ecosystem includes PaaS - Platform as a Service, the Core Platform, an AI-native enterprise operations foundation built to optimize workflows, surface insights, and accelerate value creation across portfolios; SaaS - Software as a Service, a cloud platform delivering unmatched performance, intelligence, and execution at scale; and S&C - Solutions and Consulting Suite, modular technology playbooks designed to manage, grow, and optimize company performance. With over a decade of experience supporting high-growth companies and private equity-backed platforms, Haptiq brings deep domain expertise and a proven ability to turn technology into a strategic advantage. The Opportunity As a Data Engineer within the Global Operations team, you will be responsible for managing the internal data infrastructure, building and maintaining data pipelines, and ensuring the integrity, cleanliness, and usability of data across our critical business systems. This role will play a foundational part in developing a scalable internal data capability to drive decision-making across Haptiq's operations. Responsibilities and Duties Design, build, and maintain scalable ETL/ELT pipelines to consolidate data from delivery, finance, and HR systems (e.g., Kantata, Salesforce, JIRA, HRIS platforms). Ensure consistent data hygiene, normalization, and enrichment across source systems. Develop and maintain data models and data warehouses optimized for analytics and operational reporting. Partner with business stakeholders to understand reporting needs and ensure the data structure supports actionable insights. Own the documentation of data schemas, definitions, lineage, and data quality controls. Collaborate with the Analytics, Finance, and Ops teams to build centralized reporting datasets. Monitor pipeline performance and proactively resolve data discrepancies or failures. Contribute to architectural decisions related to internal data infrastructure and tools. Requirements 3-5 years of experience as a data engineer, analytics engineer, or similar role. Strong experience with SQL, data modeling, and pipeline orchestration (e.g., Airflow, dbt). Hands-on experience with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift). Experience working with REST APIs and integrating with SaaS platforms like Salesforce, JIRA, or Workday. Proficiency in Python or another scripting language for data manipulation. Familiarity with modern data stack tools (e.g., Fivetran, Stitch, Segment). Strong understanding of data governance, documentation, and schema management. Excellent communication skills and ability to work cross-functionally. Benefits Flexible work arrangements (including hybrid mode) Great Paid Time Off (PTO) policy Comprehensive benefits package (Medical / Dental / Vision / Disability / Life) Healthcare and Dependent Care Flexible Spending Accounts (FSAs) 401(k) retirement plan Access to HSA-compatible plans Pre-tax commuter benefits Employee Assistance Program (EAP) Opportunities for professional growth and development. A supportive, dynamic, and inclusive work environment. Why Join Us? We value creative problem solvers who learn fast, work well in an open and diverse environment, and enjoy pushing the bar for success ever higher. We do work hard, but we also choose to have fun while doing it. The compensation range for this role is $75,000 to $80,000 USD

Designing Hive/HCatalog data model includes creating table definitions, file formats, compression techniques for Structured & Semi-structured data processing Implementing Spark processing based ETL frameworks Implementing Big data pipeline for Data Ingestion, Storage, Processing & Consumption Modifying the Informatica-Teradata & Unix based data pipeline Enhancing the Talend-Hive/Spark & Unix based data pipelines Develop and Deploy Scala/Python based Spark Jobs for ETL processing Strong SQL & DWH concepts

SAP S4 Data Migration Developer Duration: 6 Months Rate: Competitive Market Rate This key role is responsible for development and configuration of SAP Data Services Platform with in Client's Corporate technology to deliver a successful data conversion and migration from SAP ECC to SAP S4 as part of project Keystone. KEY RESPONSIBILITIES - Responsible for SAP Data Services development, design, job creation and execution. Responsible for efficient design, performance tuning and ensuring timely data processing, validation & verification. Responsible for creating content within SAP Data Services for both master and transaction data conversion (standard SAP and Custom data objects). Responsible for data conversion using Staging tables and work with SAP teams for data loads in SAP S4 and MDG environments. Responsible for building validation rules, scorecards and data for consumption in Information Steward pursuant to conversion rules as per Functional Specifications. Responsible to adhere to project timelines, deliverables and account for object delivery for teams involved. To take part in meetings, execute plans, design, develop custom solutions within Clients O&T Engineering scope. Work in all facets of SAP Data Migration projects with focus on SAP S4 Data Migration using SAP Data Services Platform Hands-on development experience with ETL from legacy SAP ECC environment, conversions and jobs. Demonstrate capabilities with performance tuning, handling large data sets. Understand SAP tables, fields & load processes into SAP S4, MDG systems Build validation rules, customize, and deploy Information Steward scorecards, data reconciliation and validation Be a problem solver and build robust conversion, validation per requirements. SKILLS AND EXPERIENCE 6-8 years of experience in SAP Data Services application as a developer At least 2 SAP S4 Conversion projects with DMC, Staging Tables & updating SAP Master Data Governance Good communication skills, ability to deliver key objects on time and support with testing, mock cycles. 4-5 Years development experience in SAP Data Services 4.3 Designer, Information Steward Taking ownership and ensuring high quality results Active in seeking feedback and making necessary changes Specific previous experience - Proven experience in implementing SAP Data Services in a multinational environment. Experience in design of data loads of large volumes to SAP S4 from SAP ECC Must have used HANA Staging tables Experience in developing Information Steward for Data Reconciliation & Validation (not profiling) REQUIREMENTS Adhere to work availability schedule as noted above, be on time for meeting Written and verbal communication in English

About the Company Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis' Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis' Service Transformation approach helps ‘shrink the core' through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis' core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients. About the Role Senior Level Data Architect with data analytics experience, Databricks, Pyspark, Python, ETL tools like Informatica. This is a key role that requires senior/lead with great communication skills who is very proactive with risk & issue management. Responsibilities Hands-on data analytics experience with Databricks on AWS, Pyspark and Python. Must have prior experience with migrating a data asset to the cloud using a GenAI automation option. Experience in migrating data from on-premises to AWS. Expertise in developing data models, delivering data-driven insights for business solutions. Experience in pretraining, fine-tuning, augmenting and optimizing large language models (LLMs). Experience in Designing and implementing database solutions, developing PySpark applications to extract, transform, and aggregate data, generating insights. Data Collection & Integration: Identify, gather, and consolidate data from diverse sources, including internal databases and spreadsheets ensuring data integrity and relevance. Data Cleaning & Transformation: Apply thorough data quality checks, cleaning processes, and transformations using Python (Pandas) and SQL to prepare datasets. Automation & Scalability: Develop and maintain scripts that automate repetitive data preparation tasks. Autonomy & Proactivity: Operate with minimal supervision, demonstrating initiative in problem-solving, prioritizing tasks, and continuously improving the quality and impact of your work. Qualifications 15+ years of experience as Data Analyst / Data Engineer with Databricks on AWS expertise in designing and implementing scalable, secure, and cost-efficient data solutions on AWS. Required Skills Strong proficiency in Python (Pandas, Scikit-learn, Matplotlib) and SQL, with experience working across various data formats and sources. Proven ability to automate data workflows, implement code-based best practices, and maintain documentation to ensure reproducibility and scalability. Preferred Skills Ability to manage in tight circumstances, very pro-active with risk & issue management. Requirement Clarification & Communication: Interact directly with colleagues to clarify objectives, challenge assumptions. Documentation & Best Practices: Maintain clear, concise documentation of data workflows, coding standards, and analytical methodologies to support knowledge transfer and scalability. Collaboration & Stakeholder Engagement: Work closely with colleagues who provide data, raising questions about data validity, sharing insights, and co-creating solutions that address evolving needs. Excellent communication skills for engaging with colleagues, clarifying requirements, and conveying analytical results in a meaningful, non-technical manner. Demonstrated critical thinking skills, including the willingness to question assumptions, evaluate data quality, and recommend alternative approaches when necessary. A self-directed, resourceful problem-solver who collaborates well with others while confidently managing tasks and priorities independently.