Top Data & Analytics Jobs

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Design, build, and optimize scalable ETL/ELT data pipelines using Databricks and cloud platforms. Implement data quality checks, monitor and troubleshoot jobs, audit pipelines for compliance, and collaborate with analysts and business stakeholders to define data models and support reporting.

Design, build, and maintain scalable data pipelines and ETL/ELT processes. Integrate data from multiple sources, design and manage databases/data warehouses, ensure data quality and governance, automate workflows, maintain compliance (e.g., GDPR, HIPAA), and optimize data system performance in collaboration with product and engineering teams.

Build and maintain end-to-end event-driven analytics pipelines for telemetry from robots and cloud systems. Own metrics catalog, schema evolution, data quality validation, and performant analytical models and queries to enable reporting and self-service analytics.

The Senior IT Data Engineer will design and implement enterprise data architectures, develop scalable ETL/ELT pipelines, and support data-driven initiatives for the Federal Reserve Board.

Design, build, and maintain scalable ETL pipelines using Python, SQL, and Palantir or similar platforms. Ingest structured and unstructured data from databases, APIs, and files; implement data models, cleansing, validation, monitoring, and performance optimizations; collaborate with stakeholders and document pipelines and best practices.

The Data Engineer I supports healthcare analytics projects by developing SQL workflows, data transformations, ETL processes, and reporting solutions, while collaborating with analysts and stakeholders.

The Principal Data Engineer will design and implement scalable data platforms, lead architecture discussions, and mentor teams. Requires expertise in Azure and Databricks.

Design and implement scalable, secure enterprise geospatial database solutions using Esri technology. Collaborate across project phases to configure, maintain, tune, secure, and automate databases, support ArcGIS applications, and provide technical guidance for migrations, integrations, and operational readiness for Defense/Intel clients.

Consult with customers to design and implement enterprise geospatial database solutions using Esri/ArcGIS technologies. Configure, secure, monitor, and automate databases (backup/HA/DR, performance tuning, data loading). Collaborate across teams, provide technical guidance, and support database migrations and integrations for mission-critical defense and intel applications.

Consult with customers to design and implement scalable, secure enterprise geospatial database solutions using Esri/ArcGIS technologies. Configure and maintain database environments (backup, HA/DR), monitor and tune performance, implement security and access controls, automate data workflows, and provide technical guidance across requirements, design, build, and deployment phases. Support integration with ArcGIS web, desktop, and mobile applications for Defense and Intel clients.

The Data Engineer will analyze data quality, design prediction algorithms, collaborate with the engineering team, and generate business insights.

Senior Exasol data engineer to design, build, optimize, and validate SQL-based data pipelines for healthcare analytics. Responsibilities include complex query tuning, extracting/staging from SQL Server, chart validation, applying clinical terminologies, quality measure development, and maintaining disciplined version-controlled engineering practices.

The Data Engineer will develop data pipelines and integrations, focusing on healthcare data to enhance financial operations, ensuring efficient data handling and driving impactful solutions.

The Data Engineer will manage and develop data warehousing solutions, implement ETL processes, and utilize SQL for data analysis and reporting. Experience in analytics tools and communication is essential.

Design, build, and manage batch and real-time data pipelines on GCP. Implement Terraform IAC, CI/CD, APIs, and CDC ingestion via Datastream. Build medallion architecture with Dataform/dbt, optimize BigQuery and ClickHouse models, create Airflow DAGs with monitoring, and maintain GDPR/CCPA compliance and data governance.

As a Data Engineer, you'll build data infrastructure for analytics, drive business growth strategies, and enhance personalized user experiences at Eight Sleep.

The Data Engineer will gather and process large datasets, develop algorithms, conduct data analysis, and improve predictive models for business decisions.

Design, build, and operate scalable data platforms and pipelines ingesting radar sensor data. Implement ingestion, transformation, enrichment, aggregation, and publishing workflows across relational, NoSQL, time-series, and lake/warehouse systems. Optimize PostgreSQL performance, ensure data quality, observability, and collaborate with engineering, product, and infrastructure teams to enable AI and analytics.

Design and implement data integration solutions, build data pipelines, manage cloud resources, and develop real-time data flows using AWS technologies and Snowflake.

Build, maintain, and optimize ETL/ELT data pipelines using Databricks, Apache Spark, and SQL. Support data ingestion, transformation, SSIS integration, and SQL Server development. Troubleshoot data quality, assist production support, document processes, and collaborate with analysts and stakeholders. Support data governance, HIPAA compliance, and healthcare data initiatives.

Lead the design and evolution of the enterprise data platform, establish standards, mentor teams, and collaborate across departments to deliver high-quality data products.

The role involves designing and scaling data infrastructures for private equity, developing ETL/ELT pipelines, ensuring data quality, and collaborating with various teams on data governance.

The Data Engineer will develop secure, scalable data pipelines for IRS applications, supporting complex analytics and machine learning to combat fraud and ensure compliance. Responsibilities include pipeline engineering, troubleshooting, and collaboration with data teams to create production-ready analytics solutions.

The Cloud Data Engineer will design and develop data warehouse solutions, create efficient data pipelines, collaborate with teams, and monitor system health.