Top Senior Level Data Engineer Jobs in Houston, TX

As a Big Data DevOps Lead, you will improve efficiency in Big Data infrastructure, coordinate initiatives across teams, lead architecture design efforts, ensure system reliability, and support operational tools while also providing on-call support.

The Head of International Credit and Data Science will lead the analytics team, developing risk models and credit policies to drive underwriting strategies and innovative product launches in Latin America and South East Asia. The role focuses on leveraging data to enhance business growth and improve customer financial health, while adapting solutions for diverse markets.

The Director of Consumer Insights & Data Analytics will lead efforts to understand consumer behavior, drive marketing activities through data insights, and develop tools and frameworks to optimize the customer purchase journey and enhance overall business strategies.

As a Sr. Data Engineer, you will develop and optimize ETL pipelines and scalable systems on Google Cloud Platform. Your role involves delivering high-quality solutions, collaborating with cross-functional teams, mentoring junior engineers, and leading initiatives while applying strong analytical skills in an Agile environment.

The Director, Data Integration will oversee claims data integration, ensuring accurate and timely data integration across systems. This role involves leading a team of data engineers, shaping data strategy, engaging in product development, and collaborating closely with clients to drive successful data initiatives.

The Senior Data Engineer will develop and scale a high-traffic digital ad exchange, mentor junior engineers, implement software best practices, and contribute to the architectural strategy. Responsibilities include shipping features, optimizing performance, and enhancing the overall platform.

As a Principal ML Infrastructure Engineer, you will define and drive the technical vision for Thumbtack's ML infrastructure, lead cross-functional initiatives, architect scalable ML systems, establish engineering standards, mentor teams, and align infrastructure capabilities with business objectives.