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.

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.

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.

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

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 data infrastructure, pipelines, and integrations using cloud platforms. Manage teams and client accounts, ensure data quality, security, and compliance, deploy scalable solutions (Databricks, Snowflake), mentor junior staff, and identify data-driven business opportunities.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

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.

Consult with customers to design and implement scalable, secure enterprise geospatial database solutions using Esri/ArcGIS technologies. Configure, maintain, backup, tune, and automate databases; ensure security and compliance; support deployments across web, desktop, and mobile applications.

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 Geospatial Data Engineer will design and implement cloud-based geospatial data infrastructures, optimize data processes, and lead project collaborations within the team.

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.

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.

Design, deploy, and optimize secure, scalable enterprise geospatial database solutions across cloud, on-premises, and hybrid environments. Configure, monitor, tune, secure, and automate databases; support backup/DR and provide technical guidance for migrations and integrations to enable mission-critical ArcGIS-driven systems.

Design, implement, and maintain scalable, secure geospatial database platforms supporting mission-critical Defense and Intelligence systems. Responsibilities include database design, performance tuning, high-availability and disaster recovery, automation, data security, and customer-facing technical guidance across implementation lifecycle.

Develop and manage data collection infrastructure for AI model training, utilizing cloud services and collaborating with scientists to enhance data quality and processing.

Lead design, operation, and reliability of production data pipelines in a multi-terabyte Snowflake environment. Translate client requirements into dimensional models, debug and remediate pipeline failures, evolve the data mart for event-driven and AI workflows, and improve pipeline trustworthiness via testing, CI/CD, audit logging, and documentation.

Lead design and build of a cloud-based big data analytics platform: implement analytics infrastructure, integrate streaming and batch data, develop distributed processing pipelines, manage predictive analytics models, and apply machine learning and Bayesian methods. Work involves Scala on OS X and AWS, Java and Clojure, Kafka/Samza, NoSQL, and following TDD, Agile, CI/CD practices.

The role involves leading complex initiatives in data science and machine learning, architecting solutions, mentoring staff, and presenting findings to executives.