Top Data & Analytics Jobs

The Data Engineer will develop data-driven decision analysis products, provide analytic consulting, support stakeholders with tools, and optimize defense systems for national security.

The Data Integration Lead designs and manages data ingestion pipelines, ensuring data integrity and security while supporting ETL processes in classified environments.

The Principal Data Engineer will lead development projects, design scalable data pipelines, ensure data quality, and mentor a team of engineers while collaborating with stakeholders.

As a Senior Data Engineer, you will automate processes, optimize data handling, build data products, and govern data while mentoring junior engineers.

Lead Data Engineer designs, builds, tests, and supports cloud-based data solutions. Collaborates with Agile teams on distributed, real-time, and full-stack systems using Java/Scala/Python, cloud data warehouses, big data and NoSQL technologies while mentoring peers.

Lead Data Engineer responsible for designing, developing, testing, implementing, and supporting cloud-based data solutions. Collaborate across Agile teams to build distributed, real-time data and streaming systems, mentor engineers, perform unit tests and code reviews, and leverage big data, NoSQL, and cloud data warehousing technologies.

Lead and mentor a data engineering team to design, build, test, and support cloud-based data solutions. Develop distributed, real-time and batch data pipelines using Java/Scala/Python, NoSQL and RDBMS, and cloud data warehousing (Redshift/Snowflake). Collaborate with product managers and Agile teams to deliver performant, production-ready systems.

Lead Data Engineer responsible for designing, developing, testing, implementing, and supporting cloud-based data solutions. Collaborate across Agile teams on distributed microservices, streaming, and machine learning pipelines using Java/Scala/Python, RDBMS/NoSQL, and data warehousing (Redshift/Snowflake). Mentor engineers, perform unit tests, and deliver performant production systems.

Develop and implement large-scale Big Data solutions using Java, Hadoop, NoSQL, and MPP technologies. Design and optimize distributed, data-intensive systems, participate in architecture discussions, collaborate with senior architects and offshore teams, and deliver high-quality projects. Engage with clients, conduct technical sessions, create documentation and case studies, and share knowledge across the organization.

Lead Data Engineer responsible for building, optimizing, and operating secure, scalable data pipelines and platforms. Develop and run batch and streaming pipelines, workflow orchestration (Airflow), SQL-based transformations, and production-grade Python/PySpark code. Collaborate with analysts and data scientists, own system reliability and security, mentor junior engineers, and apply enterprise-authorized AI tools with strong validation and data sensitivity practices.

Design, build, test, and maintain batch and streaming data pipelines; ingest data from varied sources; write SQL and Python transformations; monitor data quality and observability; support analytics, reporting, and data science; participate in code reviews, troubleshooting, and production support; collaborate with stakeholders to deliver scalable data solutions.

Design, implement, and maintain secure research data pipelines and architectures for sensitive datasets; automate research workflows; ensure compliance with federal regulations; support faculty and researchers on data management, onboarding, training, and secure-computing processes; coordinate documentation, incident management, and tooling recommendations to enable scalable, compliant research computing.

Design, build, and maintain cloud-based data pipelines and data products across AWS, Azure, or GCP. Advise clients on cloud data architectures, implement production data solutions, and collaborate with users, developers, and analysts to maximize data value.

Design, build, and maintain cloud-based data pipelines and data architecture on AWS/Azure/GCP. Advise clients on cloud ingestion and processing, collaborate with stakeholders, and deliver production-ready data products using modern data tools.

Design, build, and maintain cloud data pipelines and data products across AWS, Azure, or GCP. Advise clients on cloud data architecture, implement production database and ETL/streaming solutions, collaborate with stakeholders, and evaluate architectural tradeoffs to meet business needs.

Design, build, and maintain cloud data pipelines and data architecture on AWS, Azure, or GCP. Advise clients on cloud ingestion and processing strategies, collaborate with stakeholders to maximize data value, and deliver production data products using modern databases, ETL/scripting, and engineering best practices.

Design, build, and maintain cloud data pipelines and architectures on AWS/Azure/GCP. Advise clients on cloud ingestion/processing strategies, implement production data products, collaborate with stakeholders, and evaluate architectural tradeoffs.

Design, build, and maintain cloud-based data pipelines and architectures on AWS, Azure, or GCP. Advise clients on cloud data solutions, implement production data products, collaborate with stakeholders, and evaluate architectural trade-offs to meet business needs.

Design, build, and maintain cloud-based data pipelines and architectures on AWS/Azure/GCP. Advise clients on cloud data strategies, collaborate with stakeholders, implement production data products, and articulate architectural trade-offs.

Design, build, and maintain cloud data pipelines and data architecture on AWS/Azure/GCP. Advise clients on cloud-based ingestion and processing, collaborate with stakeholders, and deliver production-ready data products while evaluating architectural trade-offs.

Design and implement star-schema dimensional models and ETL pipelines, optimize SQL Server data operations, develop data processes and applications, deploy data solutions via CI/CD, and collaborate with clients to meet analytics and business requirements.

Analyze manufacturing, test, telemetry, warranty, field-return, and failure-analysis data to identify hardware quality trends and emerging issues. Build statistical analyses, dashboards, monitoring indicators, and automated reporting. Connect product performance to manufacturing processes, components, and test results; support failure investigations and corrective actions. Partner with hardware, manufacturing, quality, reliability, firmware, data engineering, and data science teams to resolve data gaps and communicate actionable recommendations.

Build and maintain production data pipelines and models using SQLMesh, BigQuery, and Python. Improve observability, reliability, and performance; support finance and revenue pipelines; participate in on-call rotation and own features end-to-end.

Design, build, and maintain data integration and ETL solutions to implement client hospital data into Meduit platforms. Develop Python scripts, SQL queries, and data models; ensure data quality, transform and map source systems, and support data warehouse and architecture improvements during client implementations.

Design, build, test, and support cloud-based data engineering solutions: ETL pipelines, data workflows, APIs, and data services. Deploy and troubleshoot in Linux/cloud environments, collaborate with platform and DevSecOps teams, ensure secure coding, document data flows, and support mission-driven programs.