Top Data Engineer Jobs in Houston, TX

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 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.

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.

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.

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.

Lead a data engineering team to design, build, and operate secure, scalable data collection, storage, processing, and analytics platforms. Develop production-quality Python code, SQL transformations, orchestration (Airflow), and streaming pipelines (Kafka/PubSub). Champion AI-assisted engineering practices, automate remediation, evaluate vendor solutions, and produce reporting in JIRA/Confluence to improve delivery, resiliency, and security.

Design, implement, and optimize large-scale data processing on Databricks and Spark. Build ETL pipelines, integrate data across AWS services (Redshift, RDS), orchestrate workflows with Airflow, and ensure data warehousing and engineering best practices. Lead and mentor development teams and collaborate with cross-functional stakeholders to drive data strategy and execution.

Design, build, and operate scalable batch and real-time data pipelines on Databricks/Azure, implement medallion architecture with Delta Lake, ensure data quality and governance via Unity Catalog, support CI/CD and production operations, and collaborate with stakeholders to deliver analytics-ready datasets for BI and ML use cases.

The Python Data Engineer will enhance data assets, drive requirements for data ingestion and access, and maintain code quality and tools in a dynamic office environment.

The Data Engineer will analyze, develop, implement, test, and support data warehouse projects. Responsibilities include project support, data validation, and enhancing data management processes, all while collaborating with team members and improving performance.

Data Engineer will develop and support data warehouse projects, analyze data integrations, work with ETL tools, and improve processes while collaborating with team members.

Lead design, development, and modernization of enterprise data platforms and cloud-native analytics solutions. Provide architecture guidance, mentor engineers, build scalable ETL/ELT pipelines, enable data governance, CI/CD/DevSecOps, and optimize performance across data lakes, warehouses, and analytics ecosystems while supporting client-facing technical efforts.

Support development, testing, and maintenance of data pipelines, ETL/ELT processes, cloud data platforms (AWS/Azure), and data models. Build scripts and queries (Python, SQL, PySpark), assist CI/CD, monitor and validate data quality, troubleshoot issues, document processes, and collaborate with teams under senior guidance.

Support development and maintenance of data pipelines, cloud-based data platforms, and analytics solutions. Build and test ETL/ELT processes, develop scripts and queries (Python, SQL, PySpark), support AWS/Azure environments, implement CI/CD and Git workflows, monitor and troubleshoot pipelines, perform data validation/QA, document processes, and collaborate with stakeholders while growing technical skills.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

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.

Build and maintain governed Silver/Gold data models and semantic assets on Databricks. Translate stakeholder KPIs into testable, reusable transformations, apply enterprise modeling standards, enable domain self-service, ensure data sensitivity and governance, and review domain-contributed models for production readiness.

The Data Engineer will execute data architecture projects, manage data ingestion processes, ensure data quality, and transition data to new systems while collaborating with investment teams.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Support design, development, and maintenance of data pipelines and infrastructure. Assist with ETL/ELT workflows, data ingestion, cleaning, validation, modeling, and warehousing. Document processes and collaborate with data teams to support analytics use cases.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Build, deploy, and operate production-grade data pipelines and data products for healthcare audiences. Design transformations, data models, and governed views using Python, SQL, Airflow, S3, Snowflake, and EMR. Implement data-quality, monitoring, and privacy-by-design controls for PHI/PII. Partner with product, analytics, and platform teams to onboard sources, support audience discovery, segmentation, activation, measurement, and troubleshoot production issues.