Top Senior Data Engineer Jobs in St. Louis, MO

Senior Data Engineer on PwC's Managed Data, Analytics & Insights team to design, build and manage advanced data ecosystems. Responsibilities include designing data solutions and scalable pipelines, solving complex problems, mentoring junior staff, maintaining high delivery standards, and building client relationships while aligning solutions to business context.

Lead design, build, and operate scalable AWS data solutions (ingestion, batch/streaming, transformation, modeling, warehouses/lakes). Collaborate with product and analytics teams, enforce data governance, debug production issues, and drive best practices, automation, and operational excellence.

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

As a Manager in Managed Services, you'll lead data ecosystems projects, mentor juniors, manage client accounts, and deliver data strategies to optimize operations and drive insights for clients.

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Lead design and implementation of cloud data platforms and ETL/ELT pipelines using Azure Fabric, ADF, Synapse, Databricks and SSIS. Modernize legacy systems, ensure security/compliance for financial data, implement CI/CD, mentor teams, optimize performance and drive data governance, quality, testing, and documentation to enable analytics and BI.

Design, build, and maintain Finance data models and scalable data pipelines on GCP. Automate workflows (Python, Airflow/Astronomer, Jenkins), ensure data governance and lineage, collaborate with stakeholders, conduct code reviews and testing, and evaluate new data sources and technologies to support financial insights.

Consult with customers to design and implement scalable, secure enterprise geospatial database solutions using Esri/ArcGIS technologies. Configure and maintain database environments (backup, HA/DR), monitor and tune performance, implement security and access controls, automate data workflows, and provide technical guidance across requirements, design, build, and deployment phases. Support integration with ArcGIS web, desktop, and mobile applications for Defense and Intel clients.

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.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

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 data engineering efforts within Technology Consulting: design data architecture and pipelines, implement AWS/Redshift and ETL solutions, support BI (QlikView/Oracle BI), coach teams, manage client relationships and SLAs, apply systems thinking to optimize outcomes and validate solutions with stakeholders.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

Lead data engineering engagements to design, build, and maintain ETL/ELT pipelines and cloud data architectures. Manage client accounts and mentor teams, leverage tools like DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate, and BI/visualization platforms to deliver analytics, performance tuning, and scalable reporting solutions.

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

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

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

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.

Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.

Lead design and development of web UI and REST middleware within an Agile team. Define requirements and acceptance criteria, implement Java/Spring and Angular solutions, build CI/CD pipelines, work with Product Owner and testers, and produce/update design documentation.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

Design, build, and maintain data pipelines and lakehouse infrastructure from ingestion through curated gold-layer objects. Monitor and resolve pipeline failures, implement data governance and quality, migrate on-prem to cloud, collaborate with BI and engineering teams, and automate/optimize ETL/ELT processes to support analytics and reporting.