Top Data Engineer Jobs in St. Louis, MO

The Senior Data Analytics Engineer analyzes and delivers business intelligence solutions, builds data pipelines, and collaborates with clients to meet their data-driven needs.

The Staff Data Engineer will enhance the data ecosystem at WeightWatchers by developing data pipelines, collaborating cross-functionally, and ensuring data quality while leading projects and technical initiatives.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.

The Senior Data Engineer will design and operate data systems, optimize data pipelines, and enhance AI workflows for legal operations. Responsibilities include data modeling, implementing governance standards, collaborating with cross-functional teams, and mentoring junior engineers.

The Senior/Staff Data Engineer will design and scale the core data platform for healthcare systems, focusing on infrastructure, tooling, and governance while mentoring engineers and collaborating with various teams.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

The Data Engineer builds and maintains scalable data pipelines in Azure, transforming raw data into reliable information for analytics. Responsibilities include designing ETL/ELT pipelines, managing Azure Data Lake, creating dashboards in Power BI, and ensuring data quality and efficiency across platforms.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

The Senior Data Engineer will design and maintain scalable cloud-native data pipelines, develop APIs, implement advanced analytics, manage AI workflows, and enhance data operations collaboratively.

Design and develop scalable Power BI semantic models and reporting solutions using Databricks Lakehouse. Implement advanced SQL, Databricks SQL, and DAX for standardized calculations, optimize performance, enforce dataset governance, build predictive models with Python/R, automate analytical workflows, and provide technical guidance and code reviews to other developers.

Build, operate, and modernize scalable data pipelines and warehouse environments for lottery reporting, analytics, and AI readiness. Improve ingestion, transformations, data models, contracts, observability, lineage, and onboarding patterns. Automate operations, troubleshoot production issues, mentor engineers, and support migration from legacy to cloud architectures while ensuring data quality, reliability, and regulatory continuity.

The Staff Data Engineer will design and maintain data systems, streamline workflow for Data Analytics and Machine Learning teams, and ensure data pipelines are efficient and reliable. Responsibilities also include driving large projects, collaborating across teams, mentoring, and supporting the company's strategy.

The Senior Staff Data Engineer at SmithRx will define technical vision, improve data engineering efficiencies, and enhance data governance while mentoring other engineers and leading cross-functional collaborations.

As a Senior Data Engineer, you will design ETLs for large customer datasets, improve integration tools, and mentor other engineers, impacting customer onboarding and data accuracy.

The Solution Engineer - Data Engineering Specialist will provide technical leadership in the financial services sector, collaborating with sales teams to demonstrate Snowflake's data platform capabilities while engaging with technical and executive stakeholders.

Lead architecture and scaling of the Databricks data warehouse and self-service data platform. Build reusable batch and streaming frameworks, enforce governance, SLOs, lineage, observability, CI/CD, and multi-tenancy. Mentor engineers, run design reviews, and ship documented patterns to enable analytics, data science, and app teams to move quickly without blocking on platform tickets.

Design, build, and maintain backend systems and data interactions for healthcare reporting. Develop APIs, data models, ETL pipelines, and interfaces; optimize performance, ensure data integrity and security, and support automated testing and CI/CD. Collaborate in Agile teams and reduce technical debt while enabling integrations with frontend and third-party systems.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

Lead design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.

Administer, stabilize, and scale Oura's global Databricks environment. Manage workspace governance, cluster policies, access control, cost monitoring, job scheduling, and incident SLAs. Onboard teams, resolve performance and reliability issues, and partner with IT and Data Architecture. Over time contribute to pipeline development, Spark optimization, CI/CD, and infrastructure-as-code to support domain-oriented data mesh initiatives.

Design, implement, and support enterprise data integrations connecting JDE, Workday, Salesforce and other platforms. Lead SQL-driven ETL/ELT pipelines, develop reusable integration frameworks, ensure data integrity and audit readiness, perform regression and production troubleshooting, and provide architectural oversight and mentorship across multiple concurrent projects.

Lead the vision and execution for scalable data governance and quality across Airbnb. Architect future-proof data ecosystems, define best practices and tooling, drive cross-functional policy implementation (privacy, legal, infosec), mentor senior engineers, and influence executive strategy to embed stewardship into the data product lifecycle.

The Senior Data Engineer will design and manage data pipelines, work with complex datasets, and collaborate with teams to enhance data product integrity and effectiveness.

Design, build, and operate large-scale AWS-based ETL pipelines using Glue/PySpark to ingest, transform, and curate multi-format data into Apache Iceberg tables. Ensure data quality, metadata management, semantic layer creation (Trino/Athena), CloudFormation deployments, documentation, and compliance within a FedRAMP federal agile environment.

Serve as a data quality and QA engineer on a federal data platform: build automated AWS Glue/Deequ data quality checks, validate schemas and ETL pipelines, create and run unit/integration tests with 90% coverage, support IV&V and UAT, perform static/security scans, produce test documentation, monitor production ETL, and collaborate with data stewards and IV&V teams.