Top Data Engineer Jobs in Austin, TX

Design, build, monitor, and optimize large-scale ETL/ELT data pipelines and data architecture. Integrate data sources, support analysts and data scientists, automate processes, ensure reliable data delivery, and write maintainable code.

The Data Engineer will manage data extraction pipelines, modernize data systems, implement monitoring tools, optimize workflows, and support compliance requirements using various tools and platforms.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

Lead data engineering projects and develop advanced architectures for large datasets. Collaborate with leadership to drive business growth and efficiency through data.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

Build and operate scalable data pipelines and analytics-ready datasets using Python, dbt, and BigQuery. Develop Looker dashboards, ensure data quality and observability, optimize performance and cost, integrate data workflows with backend services and CI/CD, and support analytics, experimentation, and production use cases.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

Design and maintain ETL pipelines and graph data models to ingest security telemetry into an AWS Neptune knowledge graph, enable ML-driven threat detection, optimize query performance, ensure data quality and compliance, and document workflows.

The Senior Data Engineer will design, implement, and optimize scalable data solutions, working with data pipelines and collaborating with cross-functional teams in healthcare.

The Senior Data Engineer will design and implement data architecture, create ETL pipelines, ensure data integrity, and support data democratization and operational tasks, collaborating with cross-functional teams to resolve data-related issues.

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 Lead Data Engineer drives enterprise-scale data solutions, oversees project scoping, and leads a team, ensuring best practices in data engineering.

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 Data Analytics Engineer develops data pipelines, maintains the analytics platform, mentors teams, and manages data sources and quality checks.

Design and maintain ETL/ELT pipelines for data, optimize workflows for analytics and machine learning, and ensure data quality and governance.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

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.