Top Data Engineer Jobs

Build and own customer data ingestion and large-scale pipelines powering AI workers. Design syncing, retrieval, and data lake systems, improve reliability/observability, partner with product/backend teams, and contribute across infrastructure to give AI agents access to enriched customer data.

The Data Engineer II role involves developing, optimizing, and managing data lakes and warehouses, ensuring data quality, implementing monitoring, and working with cloud platforms.

The Data Engineer will design and develop scalable analytics solutions using Azure Data Explorer and Power BI, modeling large datasets into insights and visualizations, while mentoring junior team members.

The Data Engineer designs and maintains scalable data products, implements quality checks, and supports analytics and reporting needs, collaborating closely with business stakeholders to ensure data reliability.

The Data Engineer II will design, build, and deploy data solutions that enable organization-wide access to data, supporting AI, Machine Learning, and business intelligence. Responsibilities include creating data pipelines, ensuring data quality, and collaborating with teams to enhance data products.

The Data Engineer will analyze, develop, implement, test, and support data warehouse projects. Responsibilities include project support, data validation, and enhancing data management processes, all while collaborating with team members and improving performance.

Data Engineer will develop and support data warehouse projects, analyze data integrations, work with ETL tools, and improve processes while collaborating with team members.

As a Senior Azure Data Engineer, you will design and build data pipelines, implement data models, and lead migrations to Azure, while ensuring optimal performance and governance.

As a Data Engineer at Calico, you'll develop infrastructure for research data, collaborate on projects, mentor junior engineers, and ensure data governance.

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 Data Engineer I, you will design, build, and maintain data systems and pipelines for analytics, requiring technical skills in programming and data architecture.

Lead and mentor a data engineering team, define technical vision and strategy, oversee data pipeline design, and collaborate with cross-functional teams.

The Data Engineer II will design and maintain ELT pipelines to support analytics across Sony Pictures. This role involves collaborating with stakeholders, delivering data models, ensuring data integrity, and driving agile project delivery within a team environment.

Design, build, test, and maintain scalable data pipelines and ETL processes. Develop data access APIs, monitor performance, diagnose database issues, produce analyses and reports, document data systems, and apply Generative AI tools responsibly to accelerate development.

Design, build, and optimize scalable data pipelines and ETL/ELT processes on cloud-native platforms (Databricks, Informatica). Implement Data Lakehouse models, ensure data quality, support CI/CD deployments, monitor production workflows, and enforce governance, security, and compliance for healthcare data alongside architects and stakeholders.

Build, maintain, and optimize data infrastructure and ETL pipelines; integrate data sources; ensure efficient, secure data collection and processing; implement quality control, documentation, and monitoring; support analytics and data science needs.

Design, build, and maintain scalable ETL/ELT pipelines and data platforms using PySpark and Azure Databricks. Parse and process structured and unstructured data, support platform scaling/monitoring/operation, and collaborate with multidisciplinary teams to deliver analytics that inform clinical and public health decision-making.

Design, build, and maintain scalable ETL/ELT pipelines and data platforms (Azure Databricks/PySpark) to process structured and unstructured data. Lead cross-functional teams, support analytical exploration, convert diverse data into usable formats, and communicate technical findings to clinical and public health stakeholders while meeting government vetting and Public Trust requirements.

Senior Databricks data engineer supporting Azure-based analytics modernization for a federal emergency management platform. Build and optimize ETL pipelines, Delta Lake/Delta Sharing integrations, data lakes/warehouses, and feature stores; prepare data for ML/MLOps; ensure data quality and security; engage stakeholders and external partners; mentor junior staff and work in Agile teams to deliver scalable data products.

Support design, development, and maintenance of scalable ETL/ELT data pipelines and modern data platforms using Azure and Microsoft Fabric. Build and optimize data models, write SQL for transformations and validation, monitor workflows, troubleshoot issues, and collaborate with analysts and stakeholders. Contribute to data governance, documentation, automation, and continuous improvement.

Build, maintain, and optimize data infrastructure and ETL pipelines. Integrate data sources, ensure secure efficient storage and quality, document processes, troubleshoot, and mentor others while supporting analytics and data science needs.

Design, build, and maintain scalable data assets and pipelines for analytics and ML; validate and ingest diverse data sources; perform exploratory data analysis and data quality checks; collaborate with cross-functional teams and produce reproducible code and documentation.

Build, validate, and operate enterprise data connector integrations and ETL pipelines (T1-T3). Maintain data quality frameworks, handle schema/API changes, produce mapping documentation, support MCP endpoint integrations for AI agents, and own production pipeline reliability and onboarding of incoming engineers throughout the engagement.

Design, build, and maintain scalable data infrastructure and ETL/ELT pipelines in cloud environments. Collaborate with data scientists and engineers to enable ML model development and feed software products. Translate stakeholder requirements, manage prototype-to-production transitions, and recommend new data technologies. Provide ad hoc engineering, POC development, and data analysis support.

The Palantir Data Engineer will design and maintain ontologies, implement data pipelines, and ensure data integrity while collaborating with product owners and teams.