Top Data Engineer Jobs

The Data Engineer will develop data pipelines, support Agile teams, ensure data performance, and collaborate to implement complex requirements for federal customers.

The Data Engineer will develop data pipelines, ensure data reliability, and support process automation while collaborating within Agile teams.

The Data Engineer will develop data pipelines, support automation, and collaborate within an Agile team to manage complex data sets, ensuring performance and reliability in data processing.

Responsible for developing data pipelines, ensuring data extraction performance, and collaborating in an Agile team to provide data-driven solutions.

This role involves developing data pipelines, ensuring data performance, automating processes, and collaborating within Agile teams to meet complex data requirements.

As a Data Engineer, you will build and own the data infrastructure, design pipelines, ensure data quality, and implement DataOps practices while collaborating closely with product and engineering teams.

As a Principal Data Engineer, you will design and implement data infrastructure and solutions, collaborating across teams to enhance healthcare data usage.

The Data Engineer will design, develop, and optimize data platforms for analytics and machine learning, ensuring high-quality data solutions.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouse structures; ingest and integrate data from multiple sources; develop data models and complex SQL transformations; implement data quality checks and monitoring; partner with cross-functional teams to deliver production-ready datasets and support analytics and data science initiatives.

Design, build, and maintain scalable data processing pipelines and infrastructure (ETL/ELT). Implement large-scale data processing (Spark, MapReduce, Kafka), support stakeholders with analysis and reporting, ensure secure multi-region data handling, and optimize data delivery for analytics and business insights.

Own and build the end-to-end data layer: extraction pipelines from messy supplier emails and PDFs, the unified data model, reliable observable pipelines, and ML-driven extraction evaluation. Drive extraction accuracy, data quality, lineage, monitoring, and automation to scale coverage and enable engineering and product to depend on the data layer.

Designs and delivers complex data solutions and pipelines for operational and analytical systems. Builds, tunes, and integrates Hadoop ecosystem components; develops containerized applications, deploys scalable ML models, and contributes to testing and performance analysis. Collaborates with stakeholders, product owners, and engineering teams to implement data requirements and troubleshoot issues.

Build and operate AndHealth's data ingestion, transformation, and warehouse infrastructure. Own scalable, idempotent pipelines, data quality and observability, orchestration and SLAs, BigQuery performance and cost optimizations, healthcare source integrations, HIPAA-compliant security, and platform-level data contracts and runbooks.

Lead cloud data engineering for federal health programs by architecting and optimizing the 1CDP Databricks lakehouse, building secure automated ingestion and ETL pipelines (Azure Data Factory, Databricks, pySpark), enforcing real-time data quality, operationalizing predictive models, ensuring SHARE IT Act compliance, and governing CI/CD and DevSecOps across cloud environments.

The candidate will improve the data ETL pipeline, build analytical tools, manage operations, and expand into new markets and asset classes.

The Data Engineer will design and manage data pipelines, develop datasets for product metrics, and collaborate with teams to ensure robust data integration and processing.

The Data & AI Engineer III will lead cloud data engineering solutions, develop data infrastructure, establish architectures, mentor team members, and secure data around cloud systems.

Design and develop Azure cloud-native data solutions, lead a team of data engineers, and enhance data pipelines with a focus on AI-powered solutions and best practices.

The Lead Data Engineer will design and build data architectures, lead a team, and develop ETL processes using cloud technologies to optimize data solutions for the U.S. business.

Design, build, and maintain cloud data warehouse infrastructure and ETL pipelines on AWS. Create reports/dashboards, collaborate with analysts and stakeholders, model data for analytics, ensure data quality, automate processes, evaluate new technologies, and mentor junior engineers.

Lead design and build scalable, low-latency, fault-tolerant data platforms and pipelines. Mentor engineers, influence data architecture and governance, build analytics stores using big-data and cloud technologies, collaborate with product and security teams, and ensure CI/CD, resiliency, testing, and performance for data-driven solutions.

Design, develop, and optimize data warehousing and ETL/ELT solutions on Microsoft SQL Server and cloud platforms. Perform data profiling, cleansing, dimensional modeling (Kimball), and performance tuning. Build semantic models and Power BI/Microsoft Fabric solutions, advise on architecture, mentor teammates, assist in pre-sales/scoping, and promote BI best practices across clients.

The Data Engineer will create innovative solutions for data management, implement and maintain data pipelines, ensure data quality, and collaborate with various teams to support business processes in healthcare.

The Forward Deployed Data Engineer will manage AI-automated data platform migration projects, ensuring timely delivery and communication with clients while utilizing proprietary tools.

As a Data Engineer, you will design and implement scalable data architectures, oversee integration and governance while collaborating on Master Data Management frameworks, to optimize data performance and drive innovation across the organization.