Top Data Engineering Jobs in Austin, TX

The Data Migration Specialist will oversee the migration of customer data from legacy systems into Prospyr, ensuring data accuracy and reliability through validation, QA checks, and collaboration with cross-functional teams to support customer onboarding and go-live processes.

Design, build, and operate Spark-based ETL pipelines on AWS. Collaborate with stakeholders to deliver reliable data products, ensure data quality and governance, optimize performance, and maintain operational excellence of the data platform.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

The Senior Quantitative Analyst is responsible for building data pipelines, conducting Monte Carlo simulations, and converting complex Excel models to code while communicating effectively with stakeholders.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead and scale the data engineering team to design, implement, and maintain cloud data warehouses, robust ETL/ELT pipelines, data sharing/integration, and BI tooling. Drive roadmap prioritization, recruitment, best practices, governance, and cross-functional collaboration to deliver secure, compliant data solutions that enable analytics and product teams.

Lead end-to-end data acquisition, ingestion, curation, and storage for foundation models (3D, video, image, audio). Ensure legal compliance, negotiate vendor contracts, develop tooling and standards for searchable, indexed datasets, and align data strategy with research and product roadmaps while managing cross-functional teams and vendor relationships.

Lead the design and implementation of algorithmic trading strategies, oversee technical infrastructures, and mentor a multidisciplinary team while managing performance analysis and risk.

Own end-to-end data pipelines for multiple clients: extract, clean, transform, model and visualize data. Build dashboards and automated workflows, apply AI where useful, and present actionable insights to non-technical stakeholders.

Client-facing data scientist supporting clinical data transfer, ETL, validation, analysis, and Power BI dashboards. Build R scripts, assist data harmonization, support internal tools and basic web interfaces while working with cross-functional teams on clinical trial data.