Top Data Engineer Jobs in Richmond, VA

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

The Senior Data Engineer handles ChowNow's data platform, collaborating with teams to enhance data availability and insights, supporting internal and customer-facing products.

Design, develop, test, implement, and support cloud-based data solutions. Collaborate across Agile teams on distributed, streaming, and full-stack systems, mentor engineers, and perform unit tests and code reviews to deliver performant data products.

Lead and mentor engineering teams to design, develop, test, and deploy cloud-based data solutions. Build distributed, real-time and batch data pipelines using big data technologies, databases, and cloud warehouses. Collaborate with product managers and peers to deliver performant, production-ready systems and ensure code quality through testing and reviews.

Lead Data Engineer designing, developing, testing, and supporting cloud-based data solutions. Collaborate across Agile teams to build distributed, streaming, and batch data pipelines, mentor engineers, and optimize performance for data warehousing and machine learning use cases.

Design, develop, test, and support cloud-based data solutions and streaming systems. Collaborate with Agile teams, mentor engineers, and ensure performant, well-tested code for large-scale financial data workloads.

The Data Engineer will develop data pipelines, collaborate with clients, advise on cloud technologies, and solve complex data problems.

The role involves migrating on-premises databases to AWS, developing Python scripts for data processing, and building AWS data pipelines. Responsibilities include supporting application teams, data modeling, and ensuring system efficiency.

Lead cross-functional Agile teams to design, build, test, and support cloud-based data solutions. Develop full-stack data engineering systems using Java/Scala/Python, RDBMS and NoSQL, Redshift/Snowflake, and distributed tools (Hadoop, Spark, Kafka). Mentor engineers, perform code reviews and unit testing, and collaborate with product managers to deliver scalable, performant data products.

Design, build, test, and support cloud-based data solutions and streaming applications. Collaborate with Agile teams, mentor engineers, implement distributed computing and data warehousing (Redshift/Snowflake), and ensure performant, well-tested code for production systems.

Seeking a Database Administrator/Data Engineer for AWS migration, responsible for migrating databases, developing Python scripts, and building data pipelines.

The Enterprise Analytics Data Engineer II will build data pipelines, optimize data platforms, ensure data quality, and collaborate with teams to create actionable insights from healthcare data.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

As a Data Engineer at LiveKit, you will manage the analytics infrastructure, develop scalable GCP-based data pipelines, and ensure effective data movement and transformation processes, while collaborating with the Analytics and engineering teams.

The Data Engineer Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.

The Data Engineer designs, builds, and supports ELT/ETL pipelines on Azure, ensuring reliability, quality, and collaboration with data stakeholders for analytics and reporting.

The Data Engineer will build and scale data systems, manage data pipelines, ensure data quality, and collaborate with cross-functional teams to utilize entertainment data effectively.

As a Data Engineer, you'll build and support scalable data pipelines and modern analytics platforms, focusing on real-time and batch data for decision-making. Responsibilities include maintaining ETL processes, data modeling, technical writing, and advocating for reliable data systems.

The Data Engineer will develop and optimize data pipelines, ensure data workflow performance, and collaborate with data teams to improve data operations and quality.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

This role involves building and maintaining data pipelines, developing data models, and ensuring data discoverability while enabling scalable analytics on blockchain data.