Top Data Engineer Jobs

As a Data Engineer II, you will build and operationalize complex data solutions, ensuring data quality and governance while supporting AI and business intelligence applications.

The Data Engineer will design, develop, and maintain data infrastructure, focusing on ETL processes, Apache Spark, Python programming, and CI/CD implementation to ensure efficient data flow and processing.

The Data Engineer designs and maintains scalable data management systems, implements data governance, and builds ETL workflows to support analytics and reporting needs.

Build and deliver end-to-end, production-grade data solutions: design and maintain scalable ETL pipelines, ingest from diverse sources, implement dbt transformations, ensure data quality and observability, optimize performance and cost, and partner with analytics, product, and engineering teams to drive business impact.

Own and scale the data platform powering ReadyOn's real-time labor OS. Design and operate batch and real-time pipelines, transformations, and data services (Python, PySpark, Airflow, Glue, Snowflake, Postgres). Build connectors, observability, data quality, and feature-store infrastructure while partnering with AI, backend, and product teams and providing technical leadership and mentorship.

Lead architecture and delivery of SoFi's data platform: build scalable data pipelines, drive cloud-native and AI-enabled tooling, enforce governance and security, mentor senior engineers, and support production on-call.

As a Lead Data Engineer, you'll design, develop, and deploy data solutions using various programming languages and cloud technologies while collaborating with Agile teams, mentoring others, and conducting code reviews.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

As a Lead Data Engineer, lead development in actionable technical solutions within Agile teams, utilizing expertise in programming, big data tech, and cloud-based data services.

The Senior Lead Data Engineer will drive major technological transformations, lead development teams, and design innovative data solutions while utilizing cloud services and big data technologies.

As a Senior Lead Data Engineer at Capital One, you'll lead a development team, utilizing various big data and cloud technologies to deliver impactful solutions. Responsibilities include collaborating with Agile teams, mentoring, and ensuring optimal code performance.

The Senior Lead Data Engineer will design, develop and support technical solutions, lead teams, and utilize various programming languages and cloud services to solve complex business problems.

Design, build, test, and support ETL/ELT data pipelines and data warehouse solutions. Integrate and cleanse data via APIs/webhooks, perform data profiling and modeling, enforce governance, maintain code in Git, troubleshoot pipeline issues, document systems, and collaborate with business and data teams.

Design, build, and maintain scalable batch and streaming data pipelines and data models using Python/PySpark, Snowflake, and cloud platforms. Optimize performance, implement orchestration (Airflow), enforce data governance/metadata standards, create data quality frameworks, support CI/CD and DevOps, monitor production pipelines, and collaborate with stakeholders to evolve the enterprise data platform.

Design, build, and maintain scalable data pipelines and AI-powered solutions using Python, Spark, Scala, Kafka, Databricks, and cloud data services. Focus on KTLO activities including vulnerability remediation, tool/version upgrades, data security, platform stability, performance tuning, and automation. Collaborate with cross-functional teams to model data, optimize queries, and support streaming and workflow orchestration (Airflow).

The AI Data Engineer will build data pipelines and semantic models, implementing Snowflake and dbt for AI products, focusing on data accuracy and usability for LLM tools.

The Data Engineer designs and maintains data pipelines and database infrastructure, ensuring reliability, optimizing data models, and supporting analytics across the organization.

Responsible for designing, building, and maintaining scalable data pipelines and transformation processes, ensuring data quality and collaborating with teams.

Design and deliver scalable data platforms and pipelines, enable data science teams, and implement best practices in automation and governance.

As a Data Engineer, you will design and maintain data infrastructure, build ingestion pipelines, and collaborate with ML and product teams for data-driven features.

The role involves designing and maintaining data pipelines, optimizing data architecture, developing visual analytics with Tableau and Power BI, project management, and collaboration with cybersecurity teams.

The Looker Data Engineer will build and optimize data models, develop reporting solutions, and support data-driven decisions using Looker and other technologies.

The Sr. Data Engineer is responsible for application development, database performance monitoring, data analytics, and ensuring compliance with quality standards.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.