Top Senior Data Engineer Jobs in Austin, TX

The Senior Data Engineer will lead BI development, enhance Power BI architecture, mentor developers, and ensure efficient delivery governance for BI projects.

The Senior Data Analytics Engineer will design and maintain data pipelines, optimize data models, and implement best practices for data governance and performance in a SaaS environment.

The Senior Data Engineer will design scalable data processing frameworks using Java and Apache Spark, manage data pipelines, and mentor junior engineers.

The Senior Data Engineer will build and manage data pipelines in Snowflake, integrate AI systems, and ensure data security and optimization while collaborating across teams to support revenue analytics.

The Senior Data Engineer will design and maintain cloud data pipelines, ensuring data quality and security while collaborating with stakeholders using DBT and AWS.

The role involves guiding customers through cloud data warehousing transformations, providing technical leadership, and assisting in production planning and deployment in various data warehousing technologies.

The Staff Data Engineer designs and builds data platforms and pipelines, ensuring data integrity and collaboration across teams for analytics and reporting.

The Senior Data Engineer leads evaluations of enterprise data integrity, focuses on modernization risks, strengthens data management practices, and ensures operational continuity throughout the data lifecycle.

The Senior Data Engineer will design and maintain data pipelines, build scalable data infrastructure, and ensure the availability of high-quality data for analytics and operations at TopDog Law.

As a Senior Data Engineer, you'll design, build, and optimize data infrastructure while collaborating with teams to enhance data flow and integration across platforms.

Design, build, and operate cloud-native data platforms and scalable pipelines using Snowflake and dbt. Lead orchestration, CI/CD, observability, and performance tuning. Collaborate on backend services and limited frontend work, mentor engineers, define modeling standards, and participate in multi-team architecture and system design.

Technical leader building scalable data pipelines, analytics infrastructure, and APIs. Own architecture, optimize large-scale query performance, mentor engineers, and partner with product and integration teams to deliver real-time and historical analytics.

As a Senior Data Engineer, you will collaborate to build Data Warehouse Solutions, develop data products, and optimize data processes using tools like dbt and Airflow. You'll ensure data integrity and work with various stakeholders to translate business requirements into technical solutions.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Design and build Spark ETL pipelines on an AWS data platform, collaborate with stakeholders to deliver reliable large-scale data products, optimize and maintain data infrastructure, ensure data quality/governance, and manage platform operations and incident response.