Top Senior Data Engineer Jobs in St. Louis, MO

Design and build data architecture, pipelines, and cloud data solutions; analyze complex problems, mentor junior staff, ensure governance and security compliance, and build client relationships.

Design and implement scalable data solutions and manage advanced data ecosystems. Analyze complex problems, build ETL/ELT pipelines and data warehouses, maintain data governance, mentor junior staff, and build client relationships while delivering high-quality managed data and analytics programs.

Design, build, and maintain data infrastructure, pipelines, and ETL solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, collaborate with clients, and apply data architecture, modeling, and workflow orchestration for scalable analytics.

Lead design and delivery of data architecture, data models, ETL/ELT pipelines, data warehouses/lakes, and security/compliance. Manage and mentor a team, partner with stakeholders, troubleshoot pipelines, and drive cloud-based, scalable data solutions.

Lead design and implementation of data architecture, pipelines, and cloud-based solutions. Manage large projects, ensure data governance and security compliance, translate stakeholder requirements into technical solutions, and coach teams while providing strategic advisory to clients.

Design and implement data architecture and scalable ETL/ELT pipelines using cloud platforms (AWS/Azure/GCP). Develop data models, ensure governance and security compliance, analyze complex problems, mentor junior staff, build client relationships, and enhance technical skills to deliver high-quality data solutions.

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop and manage data lakes and warehouses, apply data architecture and dimensional modeling, validate data quality, implement security best practices, and collaborate with clients to deliver analytics and data strategies. Mentor peers and manage growing client responsibilities as a Senior Associate.

Lead design and delivery of cloud-based data architecture, data models, ETL/ELT pipelines, data warehouses/lakes, and data security. Manage projects, mentor team members, ensure governance compliance, collaborate with stakeholders, and optimize cloud infrastructure for performance, cost, and scalability.

Lead design and implementation of data architecture and cloud-based data engineering solutions. Manage large projects, translate stakeholder requirements into technical designs, ensure data governance and security, develop data models and pipelines, advise clients strategically, and coach teams to deliver operational excellence.

Lead development of scalable data architectures, pipelines, and BI solutions to deliver strategic insights for clients. Oversee teams in managed services engagements, apply systems thinking to solve complex data problems, validate outcomes with stakeholders, and optimize performance using advanced analytics and tooling.

Lead data engineering projects and teams to design, build, and maintain ETL/ELT pipelines, cloud-based analytics (AWS/Redshift/S3/Glue), and reporting solutions. Collaborate with stakeholders to identify opportunities, implement DataStage/GoldenGate/CDC integrations, tune performance, and mentor staff to ensure project delivery and client satisfaction while promoting new technologies and best practices.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Lead architecture and reliability of the data platform, build and harden ingestion (batch and CDC), own BigQuery+dbt transformations, establish testing/observability/governance, mentor engineers, develop Python tooling and APIs, run POCs for lakehouse/open table formats, and define AI-assisted development practices.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

Design, build, and maintain scalable Spark-based ETL pipelines and computed tables in a central data lake. Integrate structured and unstructured IoT, sensor, and external data for analytics, model training, and dashboards. Collaborate with Data Science, Analytics, and ML teams to ensure reliable, high-quality customer-facing datasets.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

The Data Engineer role involves developing and maintaining data pipelines for forecasting in commercial real estate, ensuring data integrity and supporting analytics teams.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Lead development of Marriott's cloud data platform, build and own large-scale ETL pipelines on AWS and Snowflake, mentor engineers, manage service provider deliverables, ensure governance, data quality, deployment and production support, and research emerging AI/ML capabilities.

Design, build, and own Sardine's internal data platform and billing infrastructure. Implement and maintain ETL/ELT pipelines, warehouse partitioning, access controls, and data governance. Partner with stakeholders to define KPIs, produce dashboards, and ensure data quality for executive, GTM, product, and finance teams.

Design, build, and maintain scalable data pipelines and integrations across AWS, Azure, and BigQuery. Normalize, aggregate, and ensure data quality for large web and transactional datasets, leveraging APIs, ETL/orchestration tools, and big-data technologies to support analytics and BI in an e-commerce environment.