Data Engineer Jobs in St. Louis, MO

Designs, builds, and maintains secure data pipelines, ETL processes, data warehouses, and quality controls. Collects, validates, cleanses, and analyzes data; develops SQL queries, Tableau dashboards, and AWS-based solutions; investigates data integrity issues; documents standards; and partners with stakeholders to deliver technical solutions using Agile and DevOps practices.

Develop and manage Workday PSA and Financials data solutions, including conversions, transformations, integrations, reporting, APIs, EIBs, and ETL processes. Create technical documentation, perform data analysis and loading, support migrations and M&A initiatives, and ensure security, compliance, access controls, and data quality. Partner with business analysts, functional leads, engineers, and security teams while managing multiple projects and serving as a Workday data subject matter expert.

Leads architecture, administration, security, performance, availability, and lifecycle management for mission-critical on-premises Oracle databases supporting GEOINT dissemination. Designs and maintains Oracle environments, spatial data stores, RAC, Data Guard, and Grid Infrastructure; manages patching, STIG compliance, encryption, auditing, automation, and incident response. Provides technical leadership, mentorship, cross-domain support, customer briefings, database strategy, documentation, and guidance on capacity, risk, and lifecycle planning.

Architects, operates, and improves cloud data and analytics platforms and BI infrastructure. Owns platform standards, CI/CD, reliability, monitoring, incident response, security, governance, performance, and technical documentation. Leads onboarding and enables engineering and client teams through reusable patterns and guardrails. Requires production platform ownership, cloud data and BI expertise, accounting experience, scripting, SQL, troubleshooting, and cloud fundamentals.

Designs, builds, and maintains scalable data pipelines and warehouse solutions. Responsibilities include data collection, cleansing, validation, quality assurance, ETL, integrity audits, documentation, anomaly resolution, and technical requirements analysis. The engineer develops SQL-based solutions, Tableau reporting, AWS cloud data infrastructure, and automated testing processes while collaborating with customers and Agile/Scaled Agile teams. The role supports data-intensive research, supervision, regulation, payments, and economic analysis across the Federal Reserve System.

Design, deploy, secure, and optimize enterprise database environments supporting mission-critical ArcGIS systems. Responsibilities include database architecture, configuration, backup and recovery, high availability, disaster recovery, performance tuning, access controls, automation, data loading, and integration. The role operates across cloud, on-premises, and hybrid infrastructures and provides technical guidance to project teams and customers.

Design and implement secure, scalable geospatial database platforms for defense and intelligence operations. Responsibilities include database administration, performance tuning, backup and recovery, high availability, disaster recovery, access controls, compliance, automation, data integration, and technical guidance. The role also involves collaborating with customers and cross-functional teams throughout requirements, design, implementation, and deployment.

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.

Provides cybersecurity and systems engineering support across multiple networks and security domains. Responsibilities include SIEM data-flow monitoring, event and log management, configuration management, system maintenance, root-cause analysis, security patching, compliance activities, infrastructure engineering, testing, integration, and documentation. The role requires maintaining highly available services, resolving escalated issues, coordinating maintenance, and supporting secure infrastructure across Intelligence Community environments.

Provide systems engineering and cybersecurity services for Intelligence Community networks across multiple security domains and locations. Responsibilities include infrastructure design, Linux and Windows administration, network services, virtualization, cloud environments, SIEM technologies, cybersecurity troubleshooting, and root cause analysis. The role requires active Top Secret clearance, advanced systems engineering knowledge, and the ability to work independently in onsite locations.

Design and implement scalable AWS and Databricks cloud architectures, ETL/ELT pipelines, lakehouse solutions, and data platforms. Responsibilities include developing PySpark and Python workflows, optimizing Spark performance and cloud costs, managing infrastructure with Terraform, implementing CI/CD, integrating diverse data sources, and ensuring data quality, governance, security, monitoring, and compliance. The role requires onsite presence in St. Louis three days per week.

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

Develop and maintain full-stack web applications using React, TypeScript, Node.js, and NestJS. Build REST APIs, integrate relational databases and search platforms, and support CDC and streaming pipelines using Kafka, Debezium, Flink, and related technologies. Deploy cloud-native applications on Kubernetes/OpenShift through Helm and GitOps workflows. Contribute to automated testing, OpenSearch optimization, semantic search, data enrichment, observability, and Agile enterprise product development.

Designs, builds, and maintains cybersecurity log collection, management, and SIEM environments across on-premises and cloud systems. Responsibilities include configuring data pipelines, troubleshooting data flow, storage, and display issues, performing root cause analysis, maintaining uptime and versions, improving processes with automation, documenting systems, training team members, and supporting customers. The role requires occasional on-call work and collaboration across project phases.

Designs, builds, and maintains cybersecurity log collection, management, and SIEM environments across on-premises and cloud systems. Troubleshoots data flow, storage, and display issues; performs root cause analysis; ensures uptime and policy-compliant versions; automates processes; documents systems and changes; trains team members; and supports internal and external customers. The role also includes occasional rare on-call work.

Drive profitable revenue growth for data center and industrial water services across assigned accounts. Develop market strategies, identify and negotiate opportunities, close sales, manage customer relationships, analyze requirements, coordinate with sales and operations teams, document activity, support major job scopes, and control sales expenses. The role is remote and requires travel up to 50%.

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.

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.

Leads data engineering for Payment Operations monitoring transformation. Designs and maintains Snowflake pipelines, tables, stored procedures, monitoring scenarios, KPI infrastructure, and data quality controls. Serves as the Snowflake subject matter expert, documents architecture and operational processes, guides technical partners, and translates business needs into scalable data solutions. The role requires production data engineering experience, advanced SQL, Snowflake expertise, job scheduling, pipeline operations, and stakeholder communication.

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.