Data Engineer Jobs in St. Louis, MO

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Design, implement, and manage advanced data ecosystems and scalable ETL/ELT pipelines. Analyze complex problems, deliver data warehousing and governance solutions, mentor junior staff, and build client relationships while maintaining high standards and business-context awareness.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead and manage delivery of modern data ecosystems and managed data analytics programs. Oversee project planning, budgeting, quality, and client accounts. Mentor teams, drive data strategy, convert insights to business opportunities, and ensure standards and risk management across large transformations.

Develop and maintain data pipelines and ETL processes, optimize SQL and data architectures, build BI reports and dashboards (Oracle BI, QlikView, Spotfire), analyze data to produce strategic insights, support client engagements in regulated environments, and apply continuous process improvements to ensure data quality and integrity.

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

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.

Design, build, and maintain scalable Hadoop-based data processing pipelines and ETL for structured and unstructured data. Implement streaming and batch solutions (Spark, Storm, Kafka), integrate multiple data sources and NoSQL stores, optimize performance, define retention, and collaborate with product and data science teams in an Agile environment.

Build and maintain Power BI reports and Snowflake-based semantic model consumption; administer Power BI tenant (RLS, gateways, capacity); develop interactive data apps (Streamlit, React + FastAPI) hosted in Snowflake; use AI-assisted coding; collaborate with data engineers and stakeholders; manage CI/CD, version control, performance tuning, and access governance.

Design, build, and maintain Azure-based data pipelines and reusable components for reporting and analytics. Integrate, clean, transform, and optimize large-scale streaming and batch data using Databricks/Spark, ADF, and related services. Perform root-cause analysis, own pipeline reliability, and support CI/CD and DevOps practices.

Design and build scalable data architectures and ETL pipelines to support cloud migrations. Develop batch and real-time data processing, ensure data quality and security, monitor and optimize pipelines, troubleshoot migration issues, document processes, and collaborate with cross-functional teams within Agile frameworks.

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.

Early-career role to build, operate, and improve cloud data/analytics platforms (Fabric, Snowflake, Databricks). Support platform operations, CI/CD for analytics assets, onboarding for BI tools (Power BI/Tableau), runbooks, monitoring, incident response, and basic security/governance. Work under senior mentorship and contribute to automation, deployment templates, and performance triage.

Lead architecture, operation, and improvement of cloud data and analytics platforms (Fabric, Snowflake, Databricks). Own CI/CD for data assets, BI delivery (Power BI/Tableau), reliability, monitoring, incident response, security, and governance. Enable teams through standards, runbooks, and onboarding; troubleshoot performance and ensure production stability.

Build and maintain governed, activation-ready marketing data products in Snowflake. Design canonical marketing data models, event-streaming, identity resolution, quality checks, and reverse-ETL activation for marketing, CRM, paid media and AI use-cases. Enable predictive scoring, attribution, and AI-ready context layers while partnering with cross-functional stakeholders.

Build and maintain cybersecurity data pipelines, manage SIEM and log collection, perform root cause analysis, maintain system availability and configuration management, support cloud/virtualized infrastructure, and coordinate with government customers and service providers.

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.

Design, develop, and maintain scalable ETL/ELT pipelines and Snowflake data models; optimize performance; ensure data quality and integrations with CRM/ERP/billing systems; collaborate with stakeholders and evolve a Snowflake/dbt cloud-native data platform.

Operate and ensure reliability of ELT/data and integration pipelines (Airflow, Azure Integration Services). Monitor SLAs, respond to incidents, perform root cause analysis, manage Snowflake RBAC, support deployments (dbt, GitHub Actions), optimize performance, and collaborate across engineering, security, and analytics teams to maintain secure, on-time data delivery.

Lead development of scalable data platform and products: design and implement batch and streaming pipelines on GCP, enable new GCP services, build AI/ML-ready pipelines, mentor junior engineers, set engineering standards, and explore AI agents for automation and data quality.