Top Data & Analytics Jobs

Provide senior-level data engineering for analytics: resolve complex technical issues, build decision-support reports and dashboards, lead projects, prepare and integrate data, coach staff, and ensure high-quality analytics to support academic, research, and healthcare goals.

Design, build, and maintain scalable cloud data pipelines and Databricks-based data platforms. Manage Databricks clusters and Delta Lake tables, integrate with Azure services, implement CI/CD and monitoring, define data warehouse architecture and governance, collaborate with stakeholders, and support advanced analytics and future AI/ML use cases.

Design, build, and maintain data pipelines, ETL processes, and data warehousing solutions using Python and GCP/BigQuery. Ensure data quality, optimize storage and processing, support new data products, and mentor junior engineers while collaborating with the CTO and team.

Design, develop, and maintain scalable data pipelines, ETL processes, and BigQuery/GCP-based data storage. Ensure data quality, implement monitoring, assist product launches, mentor junior engineers, and collaborate closely with the CTO and team.

Design, build, operationalize, and maintain enterprise-scale data pipelines and platforms. Develop ETL/ELT workflows, parse structured and unstructured data, troubleshoot Palantir Foundry pipelines, and lead cross-functional teams to support analytics, monitoring, and scalable data solutions for mission-driven projects.

Design, implement, and maintain scalable data pipelines and storage for intelligence operations. Build ETL and real-time ingestion, optimize queries and data models, enforce data quality, governance, and security per IC standards, and collaborate with analysts and mission partners.

Lead Data Engineer responsible for building technical solutions, collaborating with Agile teams, utilizing big data technologies, and developing cloud-based data warehousing solutions to enhance user experiences.

The Lead Data Engineer will design, develop, and implement technical solutions while collaborating with Agile teams and leveraging data technologies to solve business problems.

Lead design, build, test, and support cloud-based data solutions and streaming pipelines. Collaborate with Agile teams, mentor engineers, perform code reviews and unit tests, and leverage big data, data warehousing, and cloud technologies to deliver scalable payment-network capabilities.

Design, build, test, and support cloud-based data solutions and pipelines. Collaborate with Agile teams and product managers to deliver distributed, real-time, and batch systems using big data, NoSQL, and cloud data warehousing technologies. Mentor engineers and participate in code reviews and performance tuning.

As a Data Engineer, you will design and implement data pipelines, analyze requirements, and develop software solutions to drive operational efficiency.

Lead architecture and delivery of scalable data infrastructure: design and optimize ETL/ELT pipelines, enterprise data models, and data quality frameworks. Define platform standards, mentor engineers, drive cross-functional initiatives, and partner with analytics, data science, and engineering stakeholders to ensure reliable, production-grade data assets.

Design, build, and maintain scalable data pipelines and platform infrastructure. Define data governance, monitoring, and quality standards. Partner cross-functionally with Product, Engineering, Analytics, and Data Science. Drive technical decisions, performance optimization, and infrastructure-as-code for a growing data platform supporting patients, providers, and business teams.

Design, implement, and operate data quality and governance solutions using Anomalo, Atlan, Unity Catalog and Databricks. Build automated data quality checks, validation rules, connectors, prototypes and dashboards with Python, SQL and Streamlit. Collaborate with data stewards, product and engineering teams to define CDEs, prioritize remediation, document standards, drive tool adoption, and support Agile delivery using Jira.

The Senior Data Engineer designs and maintains data systems, develops data pipelines for ingestion and analysis, and optimizes data architecture to support business needs.

The role involves gathering requirements for BI and data projects, providing documentation and support, and analyzing data to facilitate decision making and system improvements. The candidate will liaise between business units and IT, support application deployments, and drive transformation projects.

The Data Engineer will design and maintain ETL/ELT pipelines, optimize data storage, develop CI/CD pipelines, and ensure data quality and governance for federal clients.

As a Data Engineer, you will design and build scalable data pipelines and models, maintain data governance, and collaborate with AI engineers while ensuring data quality and compliance.

The Data Engineer will design and implement data architecture, develop data ingestion pipelines, collaborate with stakeholders, and improve data-related processes.

As a Data Engineer II, you will build and operationalize complex data solutions, ensuring data quality and governance while supporting AI and business intelligence applications.

As a Data Fabric Engineer, you will design and maintain data pipelines for SAP data, optimizing performance and ensuring data quality while collaborating with business stakeholders for analytics and reporting.

The Data Engineer designs and maintains scalable data management systems, implements data governance, and builds ETL workflows to support analytics and reporting needs.

Own and scale the data platform powering ReadyOn's real-time labor OS. Design and operate batch and real-time pipelines, transformations, and data services (Python, PySpark, Airflow, Glue, Snowflake, Postgres). Build connectors, observability, data quality, and feature-store infrastructure while partnering with AI, backend, and product teams and providing technical leadership and mentorship.

The Data Governance Engineer focuses on unstructured data governance, metadata cataloging, data quality management, and collaboration with stakeholders to enhance data compliance and discoverability.

The Data Governance Engineer advances data governance initiatives, focuses on metadata cataloging, lineage harvesting, and governance workflows, and collaborates on data quality and compliance.