Top Data Engineer Jobs in Austin, TX

Design, build, and maintain Databricks-based ETL/ELT pipelines and medallion-layer data products. Integrate enterprise applications (including DataStage and ServiceNow), implement data quality, governance, and operational support, and collaborate with cross-functional teams to deliver scalable, production-ready data assets for analytics, reporting, and AI.

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 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 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.

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 and build data infrastructure and pipelines using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, collaborate with clients, and apply data architecture, transformation, and analytics to deliver insights.

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.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouse architecture. Partner with cross-functional teams to define KPIs, ensure data quality and governance, own billing data infrastructure, and deliver dashboards and analytics for leadership while mentoring peers.

Design, build, and maintain scalable data pipelines and API integrations; implement data quality monitoring and alerting; troubleshoot data issues; collaborate with business stakeholders; support CI/CD processes and scale architecture for future needs.

The Data Engineer II will build and maintain data pipelines and warehouses, ensure data quality, and collaborate with cross-functional teams to support business intelligence and machine learning efforts.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

The Data Engineer will develop and implement ETL processes, design data architectures, work with data platforms, and ensure data solutions meet scalability and security needs. Responsibilities include mentoring junior engineers and collaborating with stakeholders to gather requirements and optimize data transformations.

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.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

The Principal Data Engineer will lead the technical strategy for data initiatives, focusing on real-time data platforms and collaboration with stakeholders to design efficient and innovative data architectures, ensuring data governance and compliance.

Build and operate scalable data pipelines and services to power internal products. Design data models, curate high-quality datasets, collaborate with cross-functional teams, and mentor engineers while improving platform reliability, observability, and AI-ready data layers.

Lead development and delivery of data engineering solutions for clients: design data architectures, build and maintain ETL pipelines, apply advanced analytics, implement BI visualizations, coach teams, manage managed-services SLAs, and engage stakeholders to validate and refine outcomes.

Lead data engineering engagements delivering ETL/ELT solutions, pipelines, and cloud analytics. Build and maintain architectures (DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate/CDC, S3/Glue), oversee BI and visualization, manage client accounts and teams, mentor junior staff, ensure project delivery and quality, and drive process and technology adoption.

Build and maintain internal data application tools and frameworks for a centralized cloud data lake. Collaborate with cross-functional teams and Data Engineers to add features and maintain Go-based data pipelines. Improve platform architecture for scalability, observability, and reliability while sharing knowledge and mentoring teammates.

Design, build, and productionize batch and streaming ETL/ELT pipelines and ML workflows on Azure Databricks. Implement Unity Catalog data products, MLflow model lifecycle controls, CI/CD for data/ML artifacts, and operational monitoring. Partner with cross-functional teams to modernize legacy workflows into scalable, production-ready solutions.

Build and maintain end-to-end event-driven analytics pipelines for telemetry from robots and cloud systems. Own metrics catalog, schema evolution, data quality validation, and performant analytical models and queries to enable reporting and self-service analytics.

The Data Engineer will build the data infrastructure, including ingestion pipelines and backend services, while ensuring data accessibility and quality for the company.

The Junior Data Engineer will work with data to enhance trading systems, support data warehouses, and collaborate on technical solutions with the team.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

Lead design and scaling of the data platform and analytics pipelines. Build and maintain ETL/ELT workflows, integrations, serverless data services, and reliable data models. Mentor teammates, improve automation, observability, and data governance to support analytics and operational insights.