Top Big Data Data Engineering Jobs in Austin, TX

The Senior Data Engineer will design and maintain data infrastructures, support analytics, and collaborate with stakeholders to improve data quality and governance while utilizing DBT and AWS tools.

The role involves engineering consumer-level attributes, applying statistical techniques, building dashboards, and collaborating with various teams to enhance credit-related decisions based on data insights.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

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.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

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

As the Director of Data, you will lead data engineering and analytics, develop strategies for data integration and use AI technology to drive business decisions, while managing a high-performing team.

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.

The Finance Analytics Engineer will develop analytics-ready data models, collaborate with stakeholders to design data solutions, and support Finance reporting and AI use cases.

Lead operational, strategic, and analytical initiatives to improve alerts, data coverage, and AI model ROI. Conduct R&D and data analysis, build algorithmic data streams, collaborate with cross-functional teams, and present strategic insights to inform decision-making.