Data scientist jobs in Youngstown, OH

Candidates MUST go on-site at one of the following locations Columbus, OH Cincinnati, OH Cleveland, OH Indianapolis, IN Hagerstown, MD Chicago, IL Detroit, MI Minnetonka, MN Houston, TX Charlotte, NC Akron, OH Experience: · Master's degree and 5+ years of experience related work experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, scripting languages, and packages, experience with big data analysis tools and techniques, and experience building and deploying predictive models, web scraping, and scalable data pipelines · Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling Python, R, or SAS SQL and some sort of lending experience (i.e. HELOC, Mortgage etc) is most important Excellent communication skills If a candidate has cred card experience (i.e. Discover or Bread financial ) THEY ARE A+ fit! Education: Master's degree or PhD in computer science, statistics, economics or related fields Responsibilities: · Prioritizes analytical projects based on business value and technological readiness Performs large-scale experimentation and build data-driven models to answer business questions Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence Evangelizes best practices to analytics and products teams Acts as the go-to resource for machine learning across a range of business needs Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring Provides leadership, coaching, and mentoring to team members and develops the team to work with all areas of the organization Works with stakeholders to ensure that business needs are clearly understood and that services meet those needs Anticipates and analyzes trends in technology while assessing the emerging technology's impact(s) Coaches' individuals through change and serves as a role model Skills: · Up-to-date knowledge of machine learning and data analytics tools and techniques Strong knowledge in predictive modeling methodology Experienced at leveraging both structured and unstructured data sources Willingness and ability to learn new technologies on the job Demonstrated ability to communicate complex results to technical and non-technical audiences Strategic, intellectually curious thinker with focus on outcomes Professional image with the ability to form relationships across functions Ability to train more junior analysts regarding day-to-day activities, as necessary Proven ability to lead cross-functional teams Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret) Demonstrated Expertise with at least one Data Science environment (R/RStudio, Python, SAS) and at least one database architecture (SQL, NoSQL) Financial Services background preferred

*Per the client, No C2C's!* Central Point Partners is currently interviewing candidates in the Columbus, Oh area for a large client. only GC's and USC's. This position is Hybrid (4 Days onsite)! Only candidates who are local to Columbus, Oh will be considered. Data Scientist with Hands On development experience with R, SQL & Python Summary: Our client is seeking a passionate, data-savvy Senior Data Scientist to join the Enterprise Analytics team to fuel our mission of growth through data-driven insights and opportunity discovery. This dynamic role uses a consultative approach with the business segments to dive into our customer, product, channel, and digital data to uncover opportunities for consumer experience optimization and customer value delivery. You will also enable stakeholders with actionable, intuitive performance insights that provide the business with direction for growth. The ideal candidate will have a robust mix of technical and communication skills, with a passion for optimization, data storytelling, and data visualization. You will collaborate with a centralized team of data scientists as well as teams across the organization including Product, Marketing, Data, Finance, and senior leadership. This is an exciting opportunity to be a key influencer to the company's strategic decisions and to learn and grow with our Analytics team. Notes from the manager The skills that will be critical will be Python or R and a firm understanding of SQL along with foundationally understanding what data is needed to perform studies now and in the future. For a high-level summary that should help describe what this person will be asked to do alongside their peers: I would say this person will balance analysis with development, knowing when to jump in and knowing when to step back to lend their expertise. Feature & Functional Design Data scientists are embedded in the team's designing the feature. Their main job here is to define the data tracking needed to evaluate the business case-things like event logging, Adobe tagging, third-party data ingestion, and any other tracking requirements. They are also meant to consult and outline if/when business should be bringing data into the bank and will help connect business with CDAO and IT warehousing and data engineering partners should new data need to be brought forward. Feature Engineering & Development The same data scientists stay involved as the feature moves into execution. They support all necessary functions (Amigo, QA, etc.) to ensure data tracking is in place when the feature goes live. They also begin preparing to support launch evaluation and measurement against experimentation design or business case success criteria. Feature Rollout & Performance Evaluation Owns tracking the rollout, running A/B tests, and conducting impact analysis for all features that they have been involved in the Feature & Functional Design and Feature Engineering & Development stages. They provide an unbiased view of how the feature performs against the original business case along with making objective recommendations that will provide direction for business. They will roll off once the feature has matured through business case/experiment design and evaluation. In addition to supporting feature rollouts… Data scientists on the team are also encouraged to pursue self-driven initiatives during periods when they are not actively supporting other projects. These initiatives may include designing experiments, conducting exploratory analyses, developing predictive models, or identifying new opportunities for impact. For more information about this opportunity, please contact Bill Hart at ************ AND email your resume to **********************************!

We need HANDS ON engineering leaders, not architects. MUST BE VERY SEASONED DATA SCIENCE ENGINEERS WHO IS WILLING TO DO A SHORT ONLINE TEST Can sit in Hudson Yards or Bethlehem, PA 2-3 days onsite Hybrid role - candidates must be able to work onsite in Hudson Yards, NY or Bethlehem, PA I will not entertain out of state candidates. We're looking for a very Senior Data Scientist - Agentic AI with strong hands-on experience in AI/ML, LLMs, and intelligent automation. This role will focus on building, deploying, and scaling Agentic AI systems and enterprise-level generative AI solutions that transform business operations and customer experiences. You'll work on high-visibility projects alongside senior leadership, translating cutting-edge AI research into real-world impact. Key Responsibilities: Design and deploy Agentic AI solutions to automate complex workflows. Operationalize LLMs and generative AI to process unstructured data (contracts, claims, medical records, etc.). Build autonomous agents and reasoning systems integrated into enterprise platforms. Partner with engineering and AIOps teams to move models from prototype to production. Translate research in reinforcement learning and reasoning into business-ready AI applications. Mentor junior data scientists and establish best practices for scalable AI development. What We're Looking For: PhD (2+ yrs) or Master's (10+ yrs) in Statistics, Computer Science, Engineering, or Applied Mathematics. 5+ years of hands-on AI/ML development experience. Strong programming skills in Python, PyTorch, TensorFlow, LangGraph. Proven background in machine learning, optimization, and statistical modeling. Excellent communication, leadership, and cross-functional collaboration skills.

Founded over 35 years ago, First Quality is a family-owned company that has grown from a small business in McElhattan, Pennsylvania into a group of companies, employing over 5,000 team members, while maintaining our family values and entrepreneurial spirit. With corporate offices in New York and Pennsylvania and 8 manufacturing campuses across the U.S. and Canada, the companies within the First Quality group produce high-quality personal care and household products for large retailers and healthcare organizations. Our personal care and household product portfolio includes baby diapers, wipes, feminine pads, paper towels, bath tissue, adult incontinence products, laundry detergents, fabric finishers, and dishwash solutions. In addition, we manufacture certain raw materials and components used in the manufacturing of these products, including flexible print and packaging solutions. Guided by our values of humility, unity, and integrity, we leverage advanced technology and innovation to drive growth and create new opportunities. At First Quality, you'll find a collaborative environment focused on continuous learning, professional development, and our mission to Make Things Better . We are seeking a Data Scientist for our First Quality facilities located in McElhattan, PA; Lewistown, PA; and Macon, GA. **Must have manufacturing experience with consumer goods.** The role will provide meaningful insight on how to improve our current business operations. This position will work closely with domain experts and SMEs to understand the business problem or opportunity and assess the potential of machine learning to enable accelerated performance improvements. Principle Accountabilities/Responsibilities Design, build, tune, and deploy divisional AI/ML tools that meet the agreed upon functional and non-functional requirements within the framework established by the Enterprise IT and IS departments. Perform large scale experimentation to identify hidden relationships between different data sets and engineer new features Communicate model performance & results & tradeoffs to stake holders Determine requirements that will be used to train and evolve deep learning models and algorithms Visualize information and develop engaging dashboards on the results of data analysis. Build reports and advanced dashboards to tell stories with the data. Lead, develop and deliver divisional strategies to demonstrate the: what, why and how of delivering AI/ML business outcomes Build and deploy divisional AI strategy and roadmaps that enable long-term success for the organization that aligned with the Enterprise AI strategy. Proactively mine data to identify trends and patterns and generate insights for business units and management. Mentor other stakeholders to grow in their expertise, particularly in AI / ML, and taking an active leadership role in divisional executive forums Work collaboratively with the business to maximize the probability of success of AI projects and initiatives. Identify technical areas for improvement and present detailed business cases for improvements or new areas of opportunities. Qualifications/Education/Experience Requirements PhD or master's degree in Statistics, Mathematics, Computer Science or other relevant discipline. 5+ years of experience using large scale data to solve problems and answer questions. Prior experience in the Manufacturing Industry. Skills/Competencies Requirements Experience in building and deploying predictive models and scalable data pipelines Demonstrable experience with common data science toolkits, such as Python, PySpark, R, Weka, NumPy, Pandas, scikit-learn, SpaCy/Gensim/NLTK etc. Knowledge of data warehousing concepts like ETL, dimensional modeling, and sematic/reporting layer design. Knowledge of emerging technologies such as columnar and NoSQL databases, predictive analytics, and unstructured data. Fluency in data science, analytics tools, and a selection of machine learning methods - Clustering, Regression, Decision Trees, Time Series Analysis, Natural Language Processing. Strong problem solving and decision-making skills Ability to explain deep technical information to non-technical parties Demonstrated growth mindset, enthusiastic about learning new technologies quickly and applying the gained knowledge to address business problems. Strong understanding of data governance/management concepts and practices. Strong background in systems development, including an understanding of project management methodologies and the development lifecycle. Proven history managing stakeholder relationships. Business case development. What We Offer You We believe that by continuously improving the quality of our benefits, we can help to raise the quality of life for our team members and their families. At First Quality you will receive: Competitive base salary and bonus opportunities Paid time off (three-week minimum) Medical, dental and vision starting day one 401(k) with employer match Paid parental leave Child and family care assistance (dependent care FSA with employer match up to $2500) Bundle of joy benefit (year's worth of free diapers to all team members with a new baby) Tuition assistance Wellness program with savings of up to $4,000 per year on insurance premiums ...and more! First Quality is committed to protecting information under the care of First Quality Enterprises commensurate with leading industry standards and applicable regulations. As such, First Quality provides at least annual training regarding data privacy and security to employees who, as a result of their role specifications, may come in to contact with sensitive data. First Quality is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, sexual orientation, gender identification, or protected Veteran status. For immediate consideration, please go to the Careers section at ******************** to complete our online application.

THIS IS A W2 (NOT C2C OR REFERRAL BASED) CONTRACT OPPORTUNITY REMOTE MOSTLY WITH 1 DAY/MO ONSITE IN CINCINNATI-LOCAL CANDIDATES TAKE PREFERENCE RATE: $75-85/HR WITH BENEFITS We are seeking a highly skilled Data Architect to function in a consulting capacity to analyze, redesign, and optimize a Medical Payments client's environment. The ideal candidate will have deep expertise in SQL, Azure cloud services, and modern data architecture principles. Responsibilities Design and maintain scalable, secure, and high-performing data architectures. Lead migration and modernization projects in heavy use production systems. Develop and optimize data models, schemas, and integration strategies. Implement data governance, security, and compliance standards. Collaborate with business stakeholders to translate requirements into technical solutions. Ensure data quality, consistency, and accessibility across systems. Required Qualifications Bachelor's degree in Computer Science, Information Systems, or related field. Proven experience as a Data Architect or similar role. Strong proficiency in SQL (query optimization, stored procedures, indexing). Hands-on experience with Azure cloud services for data management and analytics. Knowledge of data modeling, ETL processes, and data warehousing concepts. Familiarity with security best practices and compliance frameworks. Preferred Skills Understanding of Electronic Health Records systems. Understanding of Big Data technologies and modern data platforms outside the scope of this project.

Rate: Up to $75/hr The Opportunity: Emerald Resource Group is exclusively partnering with a Fortune 500-level Manufacturing & Technology Leader to identify a Senior Data Engineer. This organization operates globally and is currently investing heavily in a massive digital transformation to modernize how they utilize R&D and manufacturing data. This is a rare opportunity to join a stable, high-revenue enterprise environment where you will build the "data plumbing" that supports critical analytics for global operations. The Role: Architect & Build: You will design and implement robust, scalable data pipelines using the Microsoft Azure stack, ensuring data flows seamlessly from legacy on-prem sources to the cloud. Data Strategy: Partner with the Agile Data Project Manager to translate complex business requirements into technical data models. Performance Tuning: Serve as the Subject Matter Expert (SME) for query optimization and database performance, handling massive datasets generated by global labs and factories. Responsibilities: Develop and maintain ETL/ELT processes using Azure Data Factory (ADF) and Databricks. Write advanced, high-efficiency SQL queries and stored procedures. Design data lakes and data warehouses that support Power BI reporting and advanced analytics. Collaborate with Data Scientists to prepare raw data for machine learning models. Mentor junior engineers and ensure code quality through rigorous peer reviews. Requirements (Senior/Principal Level): 8+ years of hands-on experience in Data Engineering or Database Development. Deep expertise in the Azure Data Stack (Azure SQL, Azure Data Factory, Azure Synapse/Data Warehouse, Databricks). Mastery of SQL (T-SQL) and experience with Python or Scala for data manipulation. Proven experience migrating on-premise data (from ERPs like SAP) to the Cloud. Perfered: Experience in Manufacturing or Process Industries (Chemical/Pharma). Knowledge of SAP data structures (extracting data from SAP ECC or S/4HANA). Familiarity with DevOps practices (CI/CD pipelines for data).

Role: Data Engineer / Architect Contract Must Have Skills: Business Intelligence - Data Engineering Data Stage DBT Snowflake SQL JOB DESCRIPTION: Bachelor's degree in Computer Science/Information Systems or equivalent combination of education and experience. Must be able to communicate ideas both verbally and in writing to management, business and IT sponsors, and technical resources in language that is appropriate for each group. Four+ years of relevant IT experience in data engineering or related disciplines. Significant experience with at least one major relational database management system (RDBMS). Experience working with and supporting Unix/Linux and Windows systems. Proficiency in relational database modeling concepts and techniques. Solid conceptual understanding of distributed computing principles and scalable data architectures. Working knowledge of application and data security concepts, best practices, and common vulnerabilities. Experience in one or more of the following disciplines preferred: scalable data platforms and modern data architectures technologies and distributions, metadata management products, commercial ETL tools, data reporting and visualization tools, messaging systems, data warehousing, major version control systems, continuous integration/delivery tools, infrastructure automation and virtualization tools, major cloud platforms (AWS, Azure, GCP), or rest API design and development. Previous experience working with offshore teams desired. Financial industry experience, especially Regulatory Reporting, is a plus.

We're seeking a skilled Data Engineer based in Columbus, OH, to support a high-impact data initiative. The ideal candidate will have hands-on experience with Python, Databricks, SQL, and version control systems, and be comfortable building and maintaining robust, scalable data solutions. Key Responsibilities Design, implement, and optimize data pipelines and workflows within Databricks. Develop and maintain data models and SQL queries for efficient ETL processes. Partner with cross-functional teams to define data requirements and deliver business-ready solutions. Use version control systems to manage code and ensure collaborative development practices. Validate and maintain data quality, accuracy, and integrity through testing and monitoring. Required Skills Proficiency in Python for data engineering and automation. Strong, practical experience with Databricks and distributed data processing. Advanced SQL skills for data manipulation and analysis. Experience with Git or similar version control tools. Strong analytical mindset and attention to detail. Preferred Qualifications Experience with cloud platforms (AWS, Azure, or GCP). Familiarity with enterprise data lake architectures and best practices. Excellent communication skills and the ability to work independently or in team environments.

Contract-to-Hire Columbus, OH (Hybrid) Our healthcare services client is looking for an entry-level Data Engineer to join their team. You will play a pivotal role in maintaining and improving inventory and logistics management programs. Your day-to-day work will include leveraging machine learning and open-source technologies to drive improvements in data processes. Job Responsibilities Automate key processes and enhance data quality Improve injection processes and enhance machine learning capabilities Manage substitutions and allocations to streamline product ordering Work on logistics-related data engineering tasks Build and maintain ML models for predictive analytics Interface with various customer systems Collaborate on integrating AI models into customer service Qualifications Bachelor's degree in related field 0-2 years of relevant experience Proficiency in SQL and Python Understanding of GCP/BigQuery (or any cloud experience, basic certifications a plus). Knowledge of data science concepts. Business acumen and understanding (corporate experience or internship preferred). Familiarity with Tableau Strong analytical skills Attitude for collaboration and knowledge sharing Ability to present confidently in front of leaders Why Should You Apply? You will be part of custom technical training and professional development through our Elevate Program! Start your career with a Fortune 15 company! Access to cutting-edge technologies Opportunity for career growth Eight Eleven Group provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.

As an IoT Data Engineer at CurvePoint, you will design, build, and optimize the data pipelines that power our Wi-AI sensing platform. Your work will focus on reliable, low-latency data acquisition from constrained on-prem IoT devices, efficient buffering and streaming, and scalable cloud-based storage and training workflows. You will own how raw sensor data (e.g., wireless CSI, video, metadata) moves from edge devices with limited disk and compute into durable, well-structured datasets used for model training, evaluation, and auditability. You will work closely with hardware, ML, and infrastructure teams to ensure our data systems are fast, resilient, and cost-efficient at scale. Duties and Responsibilities Edge & On-Prem Data Acquisition Design and improve data capture pipelines on constrained IoT devices and host servers (limited disk, intermittent connectivity, real-time constraints). Implement buffering, compression, batching, and backpressure strategies to prevent data loss. Optimize data transfer from edge → on-prem host → cloud. Streaming & Ingestion Pipelines Build and maintain streaming or near-real-time ingestion pipelines for sensor data (e.g., CSI, video, logs, metadata). Ensure data integrity, ordering, and recoverability across failures. Design mechanisms for replay, partial re-ingestion, and audit trails. Cloud Data Pipelines & Storage Own cloud-side ingestion, storage layout, and lifecycle policies for large time-series datasets. Balance cost, durability, and performance across hot, warm, and cold storage tiers. Implement data versioning and dataset lineage to support model training and reproducibility. Training Data Enablement Structure datasets to support efficient downstream ML training, evaluation, and experimentation. Work closely with ML engineers to align data formats, schemas, and sampling strategies with training needs. Build tooling for dataset slicing, filtering, and validation. Reliability & Observability Add monitoring, metrics, and alerts around data freshness, drop rates, and pipeline health. Debug pipeline failures across edge, on-prem, and cloud environments. Continuously improve system robustness under real-world operating conditions. Cross-Functional Collaboration Partner with hardware engineers to understand sensor behavior and constraints. Collaborate with ML engineers to adapt pipelines as model and data requirements evolve. Contribute to architectural decisions as the platform scales from pilots to production deployments. Must Haves Bachelor's degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience). 3+ years of experience as a Data Engineer or Backend Engineer working with production data pipelines. Strong Python skills; experience building reliable data processing systems. Hands-on experience with streaming or near-real-time data ingestion (e.g., Kafka, Kinesis, MQTT, custom TCP/UDP pipelines). Experience working with on-prem systems or edge/IoT devices, including disk, bandwidth, or compute constraints. Familiarity with cloud storage and data lifecycle management (e.g., S3-like object stores). Strong debugging skills across distributed systems. Nice to Have Experience with IoT or sensor data (RF/CSI, video, audio, industrial telemetry). Familiarity with data compression, time-series formats, or binary data handling. Experience supporting ML training pipelines or large-scale dataset management. Exposure to containerized or GPU-enabled data processing environments. Knowledge of data governance, retention, or compliance requirements. Location Pittsburgh, PA (hybrid preferred; some on-site work with hardware teams) Salary $110,000 - $135,000 / year (depending on experience and depth in streaming + IoT systems)

The Data Engineer is a technical leader and hands-on developer responsible for designing, building, and optimizing data pipelines and infrastructure to support analytics and reporting. This role will serve as the lead developer on strategic data initiatives, ensuring scalable, high-performance solutions are delivered effectively and efficiently. The ideal candidate is self-directed, thrives in a fast-paced project environment, and is comfortable making technical decisions and architectural recommendations. The ideal candidate has prior experience in modern data platforms, most notable Databricks and the “lakehouse” architecture. They will work closely with cross-functional teams, including business stakeholders, data analysts, and engineering teams, to develop data solutions that align with enterprise strategies and business goals. Experience in the financial industry is a plus, particularly in designing secure and compliant data solutions. Responsibilities: Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data. Optimize data storage, retrieval, and processing for performance, security, and cost-efficiency. Ensure data integrity and governance by implementing robust validation, monitoring, and compliance processes. Consume and analyze data from the data pipeline to infer, predict and recommend actionable insight, which will inform operational and strategic decision making to produce better results. Empower departments and internal consumers with metrics and business intelligence to operate and direct our business, better serving our end customers. Determine technical and behavioral requirements, identify strategies as solutions, and section solutions based on resource constraints. Work with the business, process owners, and IT team members to design solutions for data and advanced analytics solutions. Perform data modeling and prepare data in databases for analysis and reporting through various analytics tools. Play a technical specialist role in championing data as a corporate asset. Provide technical expertise in collaborating with project and other IT teams, internal and external to the company. Contribute to and maintain system data standards. Research and recommend innovative, and where possible automated approaches for system data administration tasks. Identify approaches that leverage our resources and provide economies of scale. Engineer system that balances and meets performance, scalability, recoverability (including backup design), maintainability, security, high availability requirements and objectives. Skills: Databricks and related - SQL, Python, PySpark, Delta Live Tables, Data pipelines, AWS S3 object storage, Parquet/Columnar file formats, AWS Glue. Systems Analysis - The application of systems analysis techniques and procedures, including consulting with users, to determine hardware, software, platform, or system functional specifications. Time Management - Managing one's own time and the time of others. Active Listening - Giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times. Critical Thinking - Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems. Active Learning - Understanding the implications of new information for both current and future problem-solving and decision-making. Writing - Communicating effectively in writing as appropriate for the needs of the audience. Speaking - Talking to others to convey information effectively. Instructing - Teaching others how to do something. Service Orientation - Actively looking for ways to help people. Complex Problem Solving - Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions. Troubleshooting - Determining causes of operating errors and deciding what to do about it. Judgment and Decision Making - Considering the relative costs and benefits of potential actions to choose the most appropriate one. Experience and Education: High School Diploma (or GED or High School Equivalence Certificate). Associate degree or equivalent training and certification. 5+ years of experience in data engineering including SQL, data warehousing, cloud-based data platforms. Databricks experience. 2+ years Project Lead or Supervisory experience preferred. Must be legally authorized to work in the United States. We are unable to sponsor or take over sponsorship at this time.

Job Title: Data Engineer Experience: 5+ years We are seeking an experienced Data Engineer with strong expertise in PySpark and data pipeline operations. This role focuses heavily on performance tuning Spark applications, managing large-scale data pipelines, and ensuring high operational stability. The ideal candidate is a strong technical problem-solver, highly collaborative, and proactive in automation and process improvements. Key Responsibilities: Data Pipeline Management & Support Operate and support Business-as-Usual (BAU) data pipelines, ensuring stability, SLA adherence, and timely incident resolution. Identify and implement opportunities for optimization and automation across pipelines and operational workflows. Spark Development & Performance Tuning Design, develop, and optimize PySpark jobs for efficient large-scale data processing. Diagnose and resolve complex Spark performance issues such as data skew, shuffle spill, executor OOM errors, slow-running stages, and partition imbalance. Platform & Tool Management Use Databricks for Spark job orchestration, workflow automation, and cluster configuration. Debug and manage Spark on Kubernetes, addressing pod crashes, OOM kills, resource tuning, and scheduling problems. Work with MinIO/S3 storage for bucket management, permissions, and large-volume file ingestion and retrieval. Collaboration & Communication Partner with onshore business stakeholders to clarify requirements and convert them into well-defined technical tasks. Provide daily coordination and technical oversight to offshore engineering teams. Participate actively in design discussions and technical reviews. Documentation & Operational Excellence Maintain accurate and detailed documentation, runbooks, and troubleshooting guides. Contribute to process improvements that enhance operational stability and engineering efficiency. Required Skills & Qualifications: Primary Skills (Must-Have) PySpark: Advanced proficiency in transformations, performance tuning, and Spark internals. SQL: Strong analytical query design, performance tuning, and foundational data modeling (relational & dimensional). Python: Ability to write maintainable, production-grade code with a focus on modularity, automation, and reusability. Secondary Skills (Highly Desirable) Kubernetes: Experience with Spark-on-K8s, including pod diagnostics, resource configuration, and log/monitoring tools. Databricks: Hands-on experience with cluster management, workflow creation, Delta Lake optimization, and job monitoring. MinIO / S3: Familiarity with bucket configuration, policies, and efficient ingestion patterns. DevOps: Experience with Git, CI/CD, and cloud environments (Azure preferred).

This is a 6 month contract and could be 2 different positions or 1 if someone has experience in both. Hybrid on site role so need to be local. Cloud Data engineer at S4 level · Person should have minimum hands on 5 years cloud data engineering experience (Specially on Azure, Databricks and MS Fabric) and overall minimum 10 to 15 years. · Handson experience with ELT & ETL pipelines development, Data modeling, AI/ML pipeline development, and unity catalog & Purview engineering experience. · Certifications on Azure cloud would be preferred.

Local Candidates Only - No Sponsorship** A growing technology company in the Warrington, PA area is seeking a Data Engineer to join its analytics and machine learning team. This is a hands-on, engineering-focused role working with real operational time-series data-not a dashboard or BI-heavy position. We're looking for someone who's naturally curious, self-driven, and enjoys taking ownership. If you like solving real-world problems, building clean and reliable data systems, and contributing ideas that actually get implemented, you'll enjoy this environment. About the Role You will work directly with internal engineering teams to build and support production data pipelines, deploy Python-based analytics and ML components, and work with high-volume time-series data from complex systems. This is a hybrid position requiring regular on-site collaboration. What You'll Do ● Build and maintain data pipelines for time-series and operational datasets ● Deploy Python and SQL-based data processing components using cloud resources ● Troubleshoot issues, optimize performance, and support new customer implementations ● Document deployment workflows and data behaviors ● Work with engineering/domain specialists to identify opportunities for improvement ● Proactively correct inefficiencies-if something can work better, you take the initiative Required Qualifications ● 2+ years of professional experience in data engineering, data science, ML engineering, or a related field ● Strong Python and SQL skills ● Experience with time-series data or operational/industrial datasets (preferred) ● Exposure to cloud environments; Azure experience is a plus but not required ● Ability to think independently, problem-solve, and build solutions with minimal oversight ● Strong communication skills and attention to detail Local + Work Authorization Requirements (Strict) ● Must currently live within daily commuting distance of Warrington, PA (Philadelphia suburbs / Montgomery County / Bucks County / surrounding PA/NJ areas) ● No relocation, no remote-only applicants ● No sponsorship-must be authorized to work in the U.S. now and in the future These requirements are firm and help ensure strong team collaboration. What's Offered ● Competitive salary + bonus potential ● Health insurance and paid time off ● Hybrid work flexibility ● Opportunity to grow, innovate, and have a direct impact on meaningful technical work ● Supportive, engineering-first culture If This Sounds Like You We'd love to hear from local candidates who are excited about Python, data engineering, and solving real-world problems with time-series data. Work Authorization: Applicants must have valid, independent authorization to work in the United States. This position does not offer, support, or accept any form of sponsorship-whether employer, third-party, future, contingent, transfer, or otherwise. Candidates must be able to work for any employer in the U.S. without current or future sponsorship of any kind. Work authorization will be verified, and misrepresentation will result in immediate removal from consideration.

About the job: We are seeking an accomplished Tech Lead - Data Engineer to architect and drive the development of large-scale, high-performance data platforms supporting critical customer and transaction-based systems. The ideal candidate will have a strong background in data pipeline design, Hadoop ecosystem, and real-time data processing, with proven experience building data solutions that power digital products and decisioning platforms in a complex, regulated environment. As a technical leader, you will guide a team of engineers to deliver scalable, secure, and reliable data solutions enabling advanced analytics, operational efficiency, and intelligent customer experiences. Key Roles & Responsibilities Lead and oversee the end-to-end design, implementation, and optimization of data pipelines supporting key customer onboarding, transaction, and decisioning workflows. Architect and implement data ingestion, transformation, and storage frameworks leveraging Hadoop, Avro, and distributed data processing technologies. Partner with product, analytics, and technology teams to translate business requirements into scalable data engineering solutions that enhance real-time data accessibility and reliability. Provide technical leadership and mentorship to a team of data engineers, ensuring adherence to coding, performance, and data quality standards. Design and implement robust data frameworks to support next-generation customer and business product launches. Develop best practices for data governance, security, and compliance aligned with enterprise and regulatory requirements. Drive optimization of existing data pipelines and workflows for improved efficiency, scalability, and maintainability. Collaborate closely with analytics and risk modeling teams to ensure data readiness for predictive insights and strategic decision-making. Evaluate and integrate emerging data technologies to future-proof the data platform and enhance performance. Must-Have Skills 8-10 years of experience in data engineering, with at least 2-3 years in a technical leadership role. Strong expertise in the Hadoop ecosystem (HDFS, Hive, MapReduce, HBase, Pig, etc.). Experience working with Avro, Parquet, or other serialization formats. Proven ability to design and maintain ETL / ELT pipelines using tools such as Spark, Flink, Airflow, or NiFi. Proficiency in Python, Scala for large-scale data processing. Strong understanding of data modeling, data warehousing, and data lake architectures. Hands-on experience with SQL and both relational and NoSQL data stores. Cloud data platform experience with AWS. Deep understanding of data security, compliance, and governance frameworks. Excellent problem-solving, communication, and leadership skills.

Since 2006, CoStrategix has defined and implemented digital transformation initiatives, data and analytics capabilities, and digital commerce solutions for Fortune 500 and mid-market customers. CoStrategix provides thought leadership, strategy, and comprehensive end-to-end technology execution to help organizations transform and stay competitive in today's digital world. As a Gixer (employee) at CoStrategix, you will have broad exposure to diverse industries and technologies. You will work on leading-edge digital projects in areas of Data Engineering, Data Governance, Data Strategy, AI, Cloud,. Gixers operate at the leading edge of technologies, and our projects require compelling human interfaces and modern data platforms. This role is based at our culture hub in Blue Ash, Ohio. About this role: As a Data Architect at CoStrategix, you will define, orchestrate, and implement modern data platforms and architectures. This role is about understanding the current state of data ecosystems, mapping existing data flows and structures, creating an architectural blueprint, and then implementing data strategies and governance frameworks in rapid cycles. In this role, you will provide the following: Strategic & Consultative Responsibilities Act as a trusted data advisor to client stakeholders, clearly communicating trade-offs, guiding decision-making, and influencing the adoption of modern data practices. Lead stakeholder interviews and working sessions to elicit requirements, clarify use cases, and align on priorities, scope, and success metrics. Create phased data roadmaps with clear milestones, dependencies, and value outcomes (e.g., time-to-insight, cost reduction, risk reduction) and track progress against them. Provide architectural input into scoping and pricing of data engagements; ensure solutions balance value, risk, and cost, and support delivery teams in staying aligned to scope and architectural guardrails. Work closely with sales and account teams to understand customer objectives and translate them into practical, scalable data architecture and solution designs. Participate in pre-sales engagements, discovery workshops, proposal development, client presentations, and proof-of-concept activities to showcase solution feasibility and value. Data Governance, Quality & Operating Model Bring consultative competencies around data governance and data quality, helping clients define guiding principles, policies, and operating models. Lead development of comprehensive data strategies for clients that align with their business priorities. Design processes for metadata management, lineage tracking, and master data management (MDM), including stewardship roles and workflows. Establish and maintain data quality standards, metrics, and monitoring processes to ensure accurate, complete, and timely data across critical domains. Develop semantic models and curated datasets, guide adoption of data cataloging and data literacy programs. Enterprise & Solution Architecture Design and maintain conceptual, logical, and physical data architectures to support enterprise, analytical, and operational systems. Assess and recommend data platforms, cloud services, and emerging technologies to meet business needs, while collaborating with Cloud, DevOps, and Security Architects to ensure architectural alignment. Partner with Data Analysts, BI Developers, and Data Scientists to ensure data architectures enable analytics, visualization, and AI/ML initiatives. Define non-functional requirements (performance, scalability, resilience, cost, security, and compliance) for data solutions, and ensure they are addressed in the architecture and design. Maintain architecture decision records, reference architectures, and reusable patterns; define and promote standards and best practices for data modeling, integration, and consumption across teams. Implementation, Delivery & Enablement Lead the implementation of scalable, secure, and high-performing data and transformation frameworks that unify data across platforms and enable real-time, batch, and event-driven use cases. Define and enforce data design standards, patterns, and best practices during implementation to ensure consistency, maintainability, and performance. Mentor and coach engineering and analytics teams in data design principles, governance frameworks, and architectural discipline to ensure consistency and quality in delivery. Qualifications: Bachelor's Degree in Math, Statistics, Computer Science, Information Technology, or a related field 8+ years of experience in data management and architecture roles 3 to 5 years of leading data strategy, governance, or modernization efforts 3 to 5 years of pre-sales, client solutioning, and/or consulting engagement in Data Management Experience designing and implementing modern data architectures Current understanding of best practices regarding data security, governance, and regulatory compliance Experience in data modeling, data engineering, and analytics platform architecture Experience with data engineering tooling such as Databricks, Snowflake, Synapse, BigQuery, Kafka, and dbt Experience with software development, DevOps best practices, and automation methodologies Excellent leadership and negotiation skills are necessary to work effectively with colleagues at various levels of the organization and across multiple locations Communicate complex issues crisply and concisely to various levels of management Coaching and mentoring skills - ability to adapt to all levels of the organization Strong collaboration skills and excellent verbal and written communication skills About CoStrategix We make CoStrategix an awesome place to work, offering a total rewards package that includes comprehensive benefits starting on day one. Benefits include medical, dental, vision, disability, and life insurance, as well as an EAP and 401(k) retirement plan. We are a flexible hybrid workplace committed to a culture of curiosity, collaboration, learning, self-improvement, and, above all, fun. We have been named a finalist for the Cincinnati Business Courier's Best Places to Work Awards for 4 consecutive years. Do the Right Thing. Always. At CoStrategix, we are passionate about our core values. Diversity, equity & inclusion (DE&I) are part of our core values Every Gixer (employee) has an opportunity for success regardless of their race, color, 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. Creating an environment where everyone, from any background, can do their best work is the right thing to do.

Data Engineer - Job Opportunity Full time Permanent Remote - East coast only Please note this role is open for US citizens or Green Card Holders only We're looking for a Data Engineer to help build and enhance scalable data systems that power analytics, reporting, and business decision-making. This role is ideal for someone who enjoys solving complex technical challenges, optimizing data workflows, and collaborating across teams to deliver reliable, high-quality data solutions. What You'll Do Develop and maintain scalable data infrastructure, cloud-native workflows, and ETL/ELT pipelines supporting analytics and operational workloads. Transform, model, and organize data from multiple sources to enable accurate reporting and data-driven insights. Improve data quality and system performance by identifying issues, optimizing architecture, and enhancing reliability and scalability. Monitor pipelines, troubleshoot discrepancies, and resolve data or platform issues-including participating in on-call support when needed. Prototype analytical tools, automation solutions, and algorithms to support complex analysis and drive operational efficiency. Collaborate closely with BI, Finance, and cross-functional teams to deliver robust and scalable data products. Create and maintain clear, detailed documentation (configurations, specifications, test scripts, and project tracking). Contribute to Agile development processes, engineering excellence, and continuous improvement initiatives. What You Bring Bachelor's degree in Computer Science or a related technical field. 2-4 years of hands-on SQL experience (Oracle, PostgreSQL, etc.). 2-4 years of experience with Java or Groovy. 2+ years working with orchestration and ingestion tools (e.g., Airflow, Airbyte). 2+ years integrating with APIs (SOAP, REST). Experience with cloud data warehouses and modern ELT/ETL frameworks (e.g., Snowflake, Redshift, DBT) is a plus. Comfortable working in an Agile environment. Practical knowledge of version control and CI/CD workflows. Experience with automation, including unit and integration testing. Understanding of cloud storage solutions (e.g., S3, Blob Storage, Object Store). Proactive mindset with strong analytical, logical-thinking, and consultative skills. Ability to reason about design decisions and understand their broader technical impact. Strong collaboration, adaptability, and prioritization abilities. Excellent problem-solving and troubleshooting skills.

Data Engineer III About the Role We're looking for a Data Engineer III to play a key role in a large-scale data migration initiative within Client's commercial lending, underwriting, and reporting areas. This is a hands-on engineering role that blends technical depth with business analysis, focused on transforming legacy data systems into modern, scalable pipelines. What You'll Do Analyze legacy SQL, DataStage, and SAS code to extract business logic and identify key data dependencies. Document current data usage and evaluate the downstream impact of migrations. Design, build, and maintain data pipelines and management systems to support modernization goals. Collaborate with business and technology teams to translate requirements into technical solutions. Improve data quality, reliability, and performance across multiple environments. Develop backend solutions using Python, Java, or J2EE, and integrate with tools like DataStage and dbt. What You Bring 5+ years of experience with relational and non-relational databases (SQL, Snowflake, DB2, MongoDB). Strong background in legacy system analysis (SQL, DataStage, SAS). Experience with Python or Java for backend development. Proven ability to build and maintain ETL pipelines and automate data processes. Exposure to AWS, Azure, or GCP. Excellent communication and stakeholder engagement skills. Financial domain experience-especially commercial lending or regulatory reporting-is a big plus. Familiarity with Agile methodologies preferred.

Job Title - DataBricks Data Engineer **Must have 8+ years of real hands on experience** We are specifically seeking a Data Engineer-Lead with strong expertise in Databricks development. The role involves: Building and testing data pipelines using Python/Scala on Databricks Hands on experience to develop and lead the offshore team to perform development/testing work in Azure data bricks Architect data platforms using Azure services such as Azure Data Factory (ADF), Azure Databricks (ADB), Azure SQL Database, and PySpark. Collaborate with stakeholders to understand business needs and translate them into technical solutions. Provide technical leadership and guidance to the data engineering team and need to perform development. Familiar with Safe Agile concepts and good to have working experience in agile model. Develop and maintain data pipelines for efficient data movement and transformation. Onsite and offshore team communication and co-ordination. Create and update the documentation to facilitate cross-training and troubleshooting Hands on experience in scheduling tools like BMC control-M and setup jobs and test the schedules. Understand the data models and schemas to support the development work and help in creation of tables in databricks Proficiency in Azure Data Factory (ADF), Azure Databricks (ADB), SQL, NoSQL, PySpark, Power BI and other Azure data tools. Implementing automated data validation frameworks such as Great Expectations or Deequ Reconciling large-scale datasets Ensuring data reliability across both batch and streaming processes The ideal candidate will have hands-on experience with: PySpark, Scala, Delta Lake, and Unity Catalog Devops CI/CD automation Cloud-native data services Azure databricks/Oracle BMC Control-M Location: Pittsburgh, PA