Top Data Engineer Jobs

The Senior Data Engineer will design and operate data infrastructure platforms, focusing on lakehouse architecture and data workflows, while ensuring high performance and collaborating with engineering teams.

Responsible for building and operating data infrastructure platforms, ensuring scalability and performance while collaborating with teams for data platform adoption and improvements.

The Senior Data Engineer designs and maintains data architectures, develops scalable data pipelines, and ensures data governance while leading technical discussions and mentoring engineers.

The Senior Data Engineer will manage end-to-end data processes, develop ETL/ELT pipelines, and provide analytics-ready outputs using Python, Azure, and Snowflake.

The Senior Data Engineer will design, build, and optimize scalable data pipelines and maintain data architectures using PySpark and AWS, ensuring data quality and performance for analytics.

The Senior Data Engineer will focus on Data Modeling, utilizing SQL, Snowflake, and Apache Airflow to develop efficient data models and deliver data products.

Design, build, and maintain scalable cloud-native ETL/ELT pipelines and serverless workflows using Python, Airflow, and AWS. Implement dbt transformations, manage DynamoDB and other storage, enforce data quality and governance, automate CI/CD, and mentor junior engineers while collaborating with analytics, product, and creative teams.

Design and optimize BI semantic models and analytics workflows using PowerBI and Tabular Editor; build and transform large-scale datasets in BigQuery with dbt; implement CI/CD and deployment via GitHub and Azure DevOps; collaborate with stakeholders to deliver actionable visualizations and integrate Agentic AI into analytics pipelines.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

Build and maintain cloud cost attribution and cost-of-revenue models, forecast non-accelerator infrastructure demand, define unit cost metrics, surface efficiency opportunities, and create self-serve dashboards and reports to drive capacity planning and cost optimization.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.

Build and maintain Tableau dashboards and data products by extracting and validating data (SQL/Redshift), translating business requirements, supporting stakeholders, documenting/reporting, and mentoring junior analysts to drive data-informed decisions.

Lead design, build, and scale of data platform capabilities across Snowflake and AWS. Develop ETL/ELT pipelines, CI/CD and IaC, monitoring, and governance. Mentor engineers, collaborate cross-functionally, and ensure security and compliance (SOC2, PCI-DSS).

Design, build, and maintain scalable GCP data pipelines using Airflow, Dataflow (Apache Beam), and BigQuery. Ingest and transform massive datasets, optimize pipeline performance, ensure data quality/security, and collaborate with data teams to troubleshoot and deliver reliable analytics solutions.

As a Data Engineer, you'll create and maintain data pipelines, optimize data architecture, and support analytics tools for performance insights.

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.

As a Data Engineer at Figma, you'll build and maintain scalable data pipelines, optimize data models, and collaborate with teams to ensure timely data delivery.

The Lead Platform Data Engineer will design data architecture, develop scalable workflows, ensure data quality, and mentor teams in modern DataOps practices.

The Data Engineer I at Storable supports the design and maintenance of data pipelines, works with ETL processes, optimizes workflows, and collaborates with various teams to enhance data accessibility and reliability.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

The Senior Data Platform Developer will build and maintain machine learning platforms, manage AI applications, and integrate data processes for Geotab's infrastructure.

Design and maintain scalable data pipelines, ensuring accurate delivery and governance of data across the organization while collaborating with cross-functional teams.