Data scientist jobs in Madison, NJ

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 ************ ********************

Data Scientist - Pharmaceutical Analytics (PhD) 1 year Contract - Hybrid- Plainfield, NJ We're looking for a PhD-level Data Scientist with experience in the pharmaceutical industry and expertise working with commercial data sets (IQVIA, claims, prescription data). This role will drive insights that shape drug launches, market access, and patient outcomes. What You'll Do Apply machine learning & advanced analytics to pharma commercial data Deliver insights on market dynamics, physician prescribing, and patient behavior Partner with R&D, medical affairs, and commercial teams to guide strategy Build predictive models for sales effectiveness, adherence, and market forecasting What We're Looking For PhD in Data Science, Statistics, Computer Science, Bioinformatics, or related field 5+ years of pharma or healthcare analytics experience Strong skills in enterprise-class software stacks and cloud computing Deep knowledge of pharma market dynamics & healthcare systems Excellent communication skills to translate data into strategy

Data Scientist- Parsippany, NJ (Hybrid) 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 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).

Role : Sr. Azure Data Engineer with Databricks Expertise Exp : 12+ We are seeking highly skilled Azure Data Engineer with strong expertise in SQL, Python, Datawarehouse, Cloud ETL tools to join our data team. The ideal candidate will design, implement and optimize large-scale data pipeline, ensuring scalability, reliability and performance. This role involves working closely with multiple teams and business stakeholders to deliver cutting-edge data solutions. Key Responsibilities: 1. Data Pipeline Development: • Build and maintain scalable ETL/ELT pipelines using Databricks. • Leverage PySpark/Spark and SQL to transform and process large datasets. • Integrate data from multiple sources including Azure Blob Storage, ADLS and other relational/non-relational systems. 2. Collaboration & Analysis: • Work Closely with multiple teams to prepare data for dashboard and BI Tools. • Collaborate with cross-functional teams to understand business requirements and deliver tailored data solutions. 3. Performance & Optimization: • Optimize Databricks workloads for cost efficiency and performance. • Monitor and troubleshoot data pipelines to ensure reliability and accuracy. 4. Governance & Security: • Implement and manage data security, access controls and governance standards using Unity Catalog. • Ensure compliance with organizational and regulatory data policies. 5. Deployment: • Leverage Databricks Asset Bundles for seamless deployment of Databricks jobs, notebooks and configurations across environments. • Manage version control for Databricks artifacts and collaborate with team to maintain development best practices. Technical Skills: • Strong expertise in Databricks (Delta Lake, Unity Catalog, Lakehouse Architecture, Table Triggers, Delta Live Pipelines, Databricks Runtime etc.) • Proficiency in Azure Cloud Services. • Solid Understanding of Spark and PySpark for big data processing. • Experience in relational databases. • Knowledge on Databricks Asset Bundles and GitLab. Preferred Experience: • Familiarity with Databricks Runtimes and advanced configurations. • Knowledge of streaming frameworks like Spark Streaming. • Experience in developing real-time data solutions. Certifications: • Azure Data Engineer Associate or Databricks certified Data Engineer Associate certification. (Optional)

Godel Terminal is a cutting edge financial platform that puts the world's financial data at your fingertips. From Equities and SEC filings, to global news delivered in milliseconds, thousands of customers rely on Godel every day to be their guide to the world of finance. We are looking for a senior engineer in New York City to join our team and help build out live data services as well as historical data for US markets and international exchanges. This position will specifically work on new asset classes and exchanges, but will be expected to contribute to the core architecture as we expand to international markets. Our team works quickly and efficiently, we are opinionated but flexible when it's time to ship. We know what needs to be done, and how to do it. We are laser focused on not just giving our customers what they want, but exceeding their expectations. We are very proud that when someone opens the app the first time they ask: “How on earth does this work so fast”. If that sounds like a team you want to be part of, here is what we need from you: Minimum qualifications: Able to work out of our Manhattan office minimum 4 days a week 5+ years of experience in a financial or startup environment 5+ years of experience working on live data as well as historical data 3+ years of experience in Java, Python, and SQL Experience managing multiple production ETL pipelines that reliably store and validate financial data Experience launching, scaling, and improving backend services in cloud environments Experience migrating critical data across different databases Experience owning and improving critical data infrastructure Experience teaching best practices to junior developers Preferred qualifications: 5+ years of experience in a fintech startup 5+ years of experience in Java, Kafka, Python, PostgreSQL 5+ years of experience working with Websockets like RXStomp or Socket.io 5+ years of experience wrangling cloud providers like AWS, Azure, GCP, or Linode 2+ years of experience shipping and optimizing Rust applications Demonstrated experience keeping critical systems online Demonstrated creativity and resourcefulness under pressure Experience with corporate debt / bonds and commodities data Salary range begins at $150,000 and increases with experience Benefits: Health Insurance, Vision, Dental To try the product, go to *************************

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

· 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 *****************************

This is a direct hire full-time position, with a hybrid on-site 2 days a week format. YOU MUST BE A US CITIZEN OR GREEN CARD, NO OTHER STATUS TO WORK IN THE US WILL BE PERMITTED YOU MUST LIVE LOCAL TO THE AREA AND BE ABLE TO DRIVE ONSITE A MIN TWO DAYS A WEEK THE TECH STACK WILL BE: 7 years demonstrated server-side development proficiency 5 years demonstrated server-side development proficiency Programming Languages: Python (NumPy, Pandas, Oracle PL/SQL). Other non-interpreted languages like Java, C++, Rust, etc. are a plus. Must be proficient in the intermediate-advanced level of the language (concurrency, memory management, etc.) Design patterns: typical GOF patterns (Factory, Facade, Singleton, etc.) Data structures: maps, lists, arrays, etc SCM: solid Git proficiency, MS Azure DevOps (CI/CD)

Client: manufacturing company Type: direct hire Our client is a publicly traded, globally recognized technology and manufacturing organization that relies on data-driven insights to support operational excellence, strategic decision-making, and digital transformation. They are seeking a Power BI Developer to design, develop, and maintain enterprise reporting solutions, data pipelines, and data warehousing assets. This role works closely with internal stakeholders across departments to ensure reporting accuracy, data availability, and the long-term success of the company's business intelligence initiatives. The position also plays a key role in shaping BI strategy and fostering collaboration across cross-functional teams. This role is on-site five days per week in Somerset, NJ. Key Responsibilities Power BI Reporting & Administration Lead the design, development, and deployment of Power BI and SSRS reports, dashboards, and analytics assets Collaborate with business stakeholders to gather requirements and translate needs into scalable technical solutions Develop and maintain data models to ensure accuracy, consistency, and reliability Serve as the Power BI tenant administrator, partnering with security teams to maintain data protection and regulatory compliance Optimize Power BI solutions for performance, scalability, and ease of use ETL & Data Warehousing Design and maintain data warehouse structures, including schema and database layouts Develop and support ETL processes to ensure timely and accurate data ingestion Integrate data from multiple systems while ensuring quality, consistency, and completeness Work closely with database administrators to optimize data warehouse performance Troubleshoot data pipelines, ETL jobs, and warehouse-related issues as needed Training & Documentation Create and maintain technical documentation, including specifications, mappings, models, and architectural designs Document data warehouse processes for reference, troubleshooting, and ongoing maintenance Manage data definitions, lineage documentation, and data cataloging for all enterprise data models Project Management Oversee Power BI and reporting projects, offering technical guidance to the Business Intelligence team Collaborate with key business stakeholders to ensure departmental reporting needs are met Record meeting notes in Confluence and document project updates in Jira Data Governance Implement and enforce data governance policies to ensure data quality, compliance, and security Monitor report usage metrics and follow up with end users as needed to optimize adoption and effectiveness Routine IT Functions Resolve Help Desk tickets related to reporting, dashboards, and BI tools Support general software and hardware installations when needed Other Responsibilities Manage email and phone communication professionally and promptly Respond to inquiries to resolve issues, provide information, or direct to appropriate personnel Perform additional assigned duties as needed Qualifications Required Minimum of 3 years of relevant experience Bachelor's degree in Computer Science, Data Analytics, Machine Learning, or equivalent experience Experience with cloud-based BI environments (Azure, AWS, etc.) Strong understanding of data modeling, data visualization, and ETL tools (e.g., SSIS, Azure Synapse, Snowflake, Informatica) Proficiency in SQL for data extraction, manipulation, and transformation Strong knowledge of DAX Familiarity with data warehouse technologies (e.g., Azure Blob Storage, Redshift, Snowflake) Experience with Power Pivot, SSRS, Azure Synapse, or similar reporting tools Strong analytical, problem-solving, and documentation skills Excellent written and verbal communication abilities High attention to detail and strong self-review practices Effective time management and organizational skills; ability to prioritize workload Professional, adaptable, team-oriented, and able to thrive in a dynamic environment

12-15 years of overall experience, combining solution architecture and hands-on delivery. Strong client-facing skills, with the ability to lead technical conversations, manage expectations, and handle escalations calmly. Hands-on technologist capable of designing, reviewing, and, when required, building/debugging components, not limited to high-level guidance. Proficient in Data Solutions, with practical, hands-on experience in Databricks including Lakehouse architecture, ETL pipelines, analytics, and AI workloads. Strong hands-on experience with PySpark and Python for large-scale data processing and transformation. Experience designing and implementing microservices-based architectures.

About the Opportunity Our client is a global alternative investment firm in a high-growth phase, investing heavily in modernizing its enterprise data platform. With multiple investment strategies and operations across several geographies, the firm is building a scalable, front-to-back investment data environment to support portfolio management, performance reporting, and executive decision-making. This is a hands-on, senior individual contributor role for an engineer who has worked close to investment teams and understands financial and portfolio data, not just generic SaaS analytics. Who This Role Is For This role is ideal for data engineers who have experience in or alongside Private Equity, Hedge Funds, Asset Management, or Capital Markets environments and are comfortable owning complex financial data pipelines end-to-end. This is not a traditional BI, marketing, or consumer data role. Candidates coming purely from ad-tech, healthcare, or non-financial SaaS backgrounds may not find this a fit. What You'll Be Doing Design, build, and maintain scalable data pipelines supporting investment, portfolio, and fund-level data Partner closely with technology leadership and investment stakeholders to translate business and investment use cases into technical solutions Contribute to the buildout of a modern data lake / lakehouse architecture (medallion-style or similar) Integrate data across the full investment lifecycle, including: Deal and transaction data Portfolio company metrics Fund performance, AUM, and reporting data Ensure data quality, lineage, and reliability across multiple strategies and entities Operate as a senior, hands-on engineer - designing, building, and troubleshooting in the weeds when needed Required Experience 7+ years of experience as a Data Engineer or similar role Strong background supporting financial services data, ideally within: Private Equity Hedge Funds Asset Management Investment Banking / Capital Markets Experience working with complex, multi-entity datasets tied to investments, portfolios, or funds Strong SQL skills and experience building production-grade data pipelines Experience with modern cloud data platforms and architectures Comfortable working in a fast-moving, evolving environment with senior stakeholders Nice to Have Experience in environments similar to global PE firms, hedge funds, or institutional asset managers Exposure to front-to-back investment data (from source systems through reporting) Experience with Microsoft-centric data stacks (e.g., Azure, Fabric) or comparable cloud platforms Familiarity with performance, valuation, or risk-related datasets Work Environment & Compensation Hybrid role with regular collaboration in the New York office Competitive compensation aligned with senior financial services engineering talent Opportunity to help shape a firm-wide data platform during a critical growth phase

🚀 Market Data Engineer - New York | Cutting-Edge Trading Environment I'm partnered with a leading technology-driven trading team in New York looking to bring on a Market Data Engineer to support global research, trading, and infrastructure groups. This role is central to managing the capture, normalization, and distribution of massive volumes of historical market data from exchanges worldwide. What You'll Do Own large-scale, time-sensitive market data capture + normalization pipelines Improve internal data formats and downstream datasets used by research and quantitative teams Partner closely with infrastructure to ensure reliability of packet-capture systems Build robust validation, QA, and monitoring frameworks for new market data sources Provide production support, troubleshoot issues, and drive quick, effective resolutions What You Bring Experience building or maintaining large-scale ETL pipelines Strong proficiency in Python + Bash, with familiarity in C++ Solid understanding of networking fundamentals Experience with workflow/orchestration tools (Airflow, Luigi, Dagster) Exposure to distributed computing frameworks (Slurm, Celery, HTCondor, etc.) Bonus Skills Experience working with binary market data protocols (ITCH, MDP3, etc.) Understanding of high-performance filesystems and columnar storage formats

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: 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.

Our client is seeking a Data Engineer with hands-on experience in Web Scraping technologies to help build and scale a new scraping capability within their Data Engineering team. This role will work directly with Technology, Operations, and Compliance to source, structure, and deliver alternative data from websites, APIs, files, and internal systems. This is a unique opportunity to shape a new service offering and grow into a senior engineering role as the platform evolves. Responsibilities Develop scalable Web Scraping solutions using AI-assisted tools, Python frameworks, and modern scraping libraries. Manage the full lifecycle of scraping requests, including intake, feasibility assessment, site access evaluation, extraction approach, data storage, validation, entitlement, and ongoing monitoring. Coordinate with Compliance to review Terms of Use, secure approvals, and ensure all scrapes adhere to regulatory and internal policy guidelines. Build and support AWS-based data pipelines using tools such as Cron, Glue, EventBridge, Lambda, Python ETL, and Redshift. Normalize and standardize raw, vendor, and internal datasets for consistent consumption across the firm. Implement data quality checks and monitoring to ensure the reliability, historical continuity, and operational stability of scraped datasets. Provide operational support, troubleshoot issues, respond to inquiries about scrape behavior or data anomalies, and maintain strong communication with users. Promote data engineering best practices, including automation, documentation, repeatable workflows, and scalable design patterns. Required Qualifications Bachelor's degree in Computer Science, Engineering, Mathematics, or related field. 2-5 years of experience in a similar Data Engineering or Web Scraping role. Capital markets knowledge with familiarity across asset classes and experience supporting trading systems. Strong hands-on experience with AWS services (S3, Lambda, EventBridge, Cron, Glue, Redshift). Proficiency with modern Web Scraping frameworks (Scrapy, BeautifulSoup, Selenium, Playwright). Strong Python programming skills and experience with SQL and NoSQL databases. Familiarity with market data and time series datasets (Bloomberg, Refinitiv) is a plus. Experience with DevOps/IaC tooling such as Terraform or CloudFormation is desirable.

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.

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)

Our client is a growing Fintech software company Headquarted in New York, NY. They have several hundred employees and are in growth mode. They are currently looking for a Senior Data Engineer w/ 6+ years of overall professional experience. Qualified candidates will have hands-on experience with Python (6 years), SQL (6 years), DBT (3 years), AWS (Lambda, Glue), Airflow and Snowflake (3 years). BSCS and good CS fundamentals. The Senior Data Engineer will work in a collaborative team environment and will be responsible for building, optimizing and scaling ETL Data Pipelines, DBT models and Datawarehousing. Excellent communication and organizational skills are expected. This role features competitive base salary, equity, 401(k) with company match and many other attractive perks. Please send your resume to ******************* for immediate consideration.

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