Top Data Engineer Jobs

Design, build and maintain data pipelines, warehouses and lakes; implement processing and analysis algorithms; collaborate with data scientists on ML deployment; lead/coach teams and influence stakeholders to ensure secure, accurate, and scalable data platforms.

The intern will assist the Data Operations team in optimizing data workflows, developing automation scripts, and maintaining data systems while gaining hands-on experience.

The Data Engineer will design and maintain scalable data pipelines, integrate APIs, support ML teams, and optimize data systems for performance and reliability.

Join Avride as a Data Analytics Engineer to build ETL pipelines, manage datasets, write SQL queries, and create dashboards for data insights.

The Senior Data Engineer will manage data pipelines, ensuring data quality and optimizing ML workflows while supporting multiple engineering teams across locations.

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

Design, build, and operationalize large-scale data platforms and pipelines on GCP. Mentor engineers, ensure data quality and system performance, and deploy production data solutions using BigQuery, Dataflow, Airflow, Terraform, and related tools.

Lead design and implementation of batch and streaming data pipelines, build data models, implement data quality and testing, manage orchestration and IaC, mentor engineers, and communicate technical direction and tradeoffs to stakeholders.

Develop, convert, and refine customer distribution network models via ETL processes. Extract, transform, validate, and load geospatial and network data; tune SQL, troubleshoot ETL performance, run data quality checks, document processes, conduct workshops, and collaborate with customers and cross-functional teams to deliver accurate ADMS/NMM models.

The Data Engineer will clean, manage, and analyze datasets, automate ETL processes, and collaborate with traders and software engineers to derive insights.

Responsible for implementing AI data pipelines, developing AI-driven systems, and ensuring the reliability and scalability of data solutions while mentoring junior team members and collaborating with cross-functional teams.

Design, build, and deploy Python-based interactive data applications and workflow automations. Implement data pipelines and ETL/ELT processes (SQL, Snowflake), integrate APIs, ensure production readiness, collaborate with stakeholders, and contribute to architecture, code reviews, and monitoring.

Design, build, and maintain scalable data pipelines and platforms; ensure data quality and performance; collaborate with stakeholders and mentor engineers to deliver analytics and production data solutions.

Own and build a production Snowflake analytics platform and ELT pipelines from GTM and product sources, implement dbt transformations and CI/CD, enable self-service BI in Power BI/Tableau, ensure data quality/security/compliance, and present insights to leadership.

The Data Integration Engineer will design, build, and maintain data pipelines and integrations across AWS and Snowflake, ensuring data quality and security while optimizing performance. They will collaborate with various technical teams to implement scalable solutions and document processes for maintainability.

The Data Engineer will design, build, and optimize data pipelines, ETL workflows, and large-scale data solutions, with strong SQL expertise required.

Lead design and optimization of enterprise Snowflake data warehouses, build scalable Python data pipelines, implement IaC on AWS, enforce data security, drive DataOps/CI-CD, and collaborate across agile teams to support mortgage analytics and financial systems.

Design and maintain technical infrastructure for data analysis, collaborate with stakeholders, and develop data visualization tools.

Implement client revenue cycle data into company systems by creating and configuring ETL processes, building data transformations and logical/physical schemas, documenting solutions in Jira, attending client meetings, and mentoring team members to ensure post-implementation data integrity.

Lead design and evolve cloud-native database and data access architectures, set data engineering standards, lead integrations and cross-functional projects, mentor engineers, and drive operational excellence, monitoring, resilience, and GenAI-assisted automation.

Lead the design and development of scalable data solutions, improve Ad Relevancy, and mentor junior engineers in a collaborative environment.

Design and operate petabyte-scale data infrastructure: build high-throughput streaming pipelines, architect a tiered Data Lakehouse, automate orchestration and backfills, optimize embedded team data schemas, manage Kubernetes stateful deployments, and enforce data quality, governance, and access controls.

As a Senior Data Engineer, you will build complex data solutions and pipelines, support analytics growth, and educate users. Collaboration and advanced technical skills are essential.

Design, build, and maintain scalable ETL/ELT pipelines and Power BI dashboards; write testable Python, R, and SQL code; enforce version control and engineering standards; partner with data scientists to productionize analytics; explore AI tools; and mentor junior staff.

The Senior Data Engineer will design and maintain scalable data pipelines and analytics systems for product and marketing insights, ensuring data quality and collaborating with various teams.