Top Data Engineer Jobs

As a Data Engineer, you will architect and maintain the data systems, create pipelines and integrations, and ensure data quality for analytics and reporting.

As a Founding Data Engineer, you'll build ETL pipelines, design scalable data models on AWS, and process complex healthcare data to improve patient care.

Build and maintain ETL pipelines and workflows to process cloud billing data. Design data storage systems and develop validation systems to ensure data quality.

As a Senior Data Engineer, you'll design data pipelines, develop analytics ecosystems, and integrate AI/ML capabilities for mission-driven projects, guiding teams in an agile environment.

The Data Engineer will design and build data pipelines and platforms, mentor teams, and implement AI/ML solutions for various high-impact projects, primarily in secure environments.

The Data Engineer will design and implement scalable data pipelines, collaborate on data workflows, and ensure data quality, working within a cross-functional team to optimize data processes.

The Data Engineer will design, build, and maintain data pipelines and cloud solutions, ensuring data quality and supporting analytics. Key tasks involve developing ETL processes, managing CI/CD, and collaborating with teams for data integration.

As a Data Engineer I, you'll build and maintain data pipelines for climate and weather datasets, working closely with senior engineers and contributing to design discussions and documentation.

As a Data Engineer, you will build and maintain data ingestion pipelines, develop data transformations, and migrate SQL Server processes to Azure-native solutions, supporting marketing campaigns and analytics teams.

The Data Engineer is responsible for building and maintaining data pipelines, ensuring data quality and reliability, and collaborating with various teams on data needs. This involves working with AWS tools and programming in Python and SQL to support analytics and infrastructure.

Design, build, and maintain scalable data pipelines and platforms for banking data. Collaborate with teams to ensure secure, reliable data products.

Build and maintain batch and streaming data pipelines, transform and document datasets, implement data quality and observability, support ML training datasets, and collaborate with product and analytics partners to deliver reliable, production-ready data products that enable reporting and machine learning use cases.

Design, implement, and optimize scalable data pipelines and infrastructure on AWS. Maintain ETL artifacts, provide Tier 3 support, collaborate with stakeholders and a product team, document dataflows, and occasionally support off-hours deployments.

Build and operate Vanguard's Microsoft Fabric data layer: design OneLake lakehouses/warehouses, pipelines, notebooks, and real-time ingestion; implement CI/CD, Terraform IaC, monitoring, governance, security, and cross-cloud integrations; serve as Tier-3 escalation and enable AI-ready semantic datasets for Power BI and agent consumption.

Design, build, test, and maintain data architectures, database systems, and pipelines using GCP and BigQuery. Optimize data retrieval, automate processes, redesign infrastructure for scalability, collaborate with stakeholders, and deliver analytics tools that provide actionable business insights.

Support government customer by extracting, cleaning, modeling, and analyzing large datasets; automate ETL and statistical workflows; develop/validate data models and novel statistical approaches; produce reports, visualizations, and data packages; operate independently on data science/engineering tasks and support capability acquisition.

Design, build, and maintain scalable batch and streaming data pipelines, storage, and integrations on AWS. Own features end-to-end, write testable code, collaborate with cross-functional teams, support data scientists with semantic models, ensure data quality, and occasionally travel to customer sites for deployment and integration.

Build and maintain scalable, reliable data pipelines and ingestion processes; support data integration, quality, governance, and cloud-based analytics platforms; troubleshoot partner/customer data environments; document standards and reference architectures; automate processes and ensure security and compliance for enterprise data solutions.

Design, build, and maintain Databricks-based data pipelines and ETL/ELT processes using Python and SQL. Optimize workflows for performance and cost, support data modeling and cloud integrations (Azure/AWS/GCP), monitor and troubleshoot pipelines, document best practices, and collaborate with cross-functional teams.

Design, build, and maintain scalable data pipelines and models; collaborate with analysts and data scientists to provision prepared datasets; implement data quality, governance and monitoring; recommend technologies; lead root-cause analysis, code reviews and testing; mentor teammates and support production data environments.

Lead design and delivery of Microsoft Fabric and Azure-based data lakehouse and warehouse solutions. Own data ingestion, ETL, modeling, governance, security, CI/CD, and Power BI integration. Architect GenAI/RAG solutions, mentor a small engineering team, define standards and playbooks, and partner with business and tech stakeholders to execute multiple concurrent implementations.

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.

Design, build, and operate data pipelines for structured and unstructured sources, performing ingestion, cleaning, transformation, quality checks, lineage capture, and monitoring. Ensure compliance with DoD governance and security, troubleshoot pipeline failures, maintain runbooks, and collaborate with stakeholders to deliver scalable, governed data products on Army enterprise platforms using Vantage/Foundry tools.

Support and maintain data ingestion, ETL, and normalization pipelines into Azure SQL and Azure Data Lake using ADF, Databricks, SQL Data Tools, and Python. Ensure data quality and security, assist client onboarding, create technical database documentation, and collaborate with data and client services teams to support higher-education partners.

We're seeking a Data Engineer with 5+ years of experience to build data processing solutions using Python, design data models, and process large data streams while ensuring high performance across various data technologies.