About this role
Staff Data Engineer
Location: Oakland, California Job ID: 22652
Company Overview Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Credit Karma has grown significantly through the years: we now have more than 1,700 employees across our offices in Oakland, Charlotte, Culver City, San Diego, London and New York City.
About the Role
We are looking for a Staff Data Engineer to build scalable data and software solutions that power a wide range of use cases across Credit Karma. In this role, you will work cross-functionally with Product Management, Data Architects, Data Scientists, Product Analysts, Software Engineers, and other Data Engineers to translate business and product needs into robust, production-grade systems. You will design and develop data warehouses, data models, pipelines, and reusable frameworks, while also contributing to the broader infrastructure and services that enable reliable and efficient data processing and experiment execution at scale. This is an end-to-end engineering role with a strong emphasis on software engineering fundamentals. Beyond building data pipelines and datasets, you will be expected to apply solid engineering practices to develop scalable, maintainable systems, and contribute to shared platforms. This role is ideal for engineers who are passionate about building reliable systems with data at the core, and who are interested in growing across both data engineering and software/platform engineering domains.
Responsibilities
- Build End-to-End Data & Software Systems
- Design and develop scalable, production-grade systems across the data lifecycle, including data ingestion, processing, modeling, and serving
- Build and maintain robust data pipelines (batch and streaming) using modern data technologies
- Apply strong software engineering principles to ensure systems are reliable, testable, and maintainable
- Develop Data Products, Models & Frameworks
- Build well-structured, reusable datasets and data models that power analytics, applications, and downstream systems
- Develop and enhance frameworks that enable scalable data processing and reduce duplication across teams
- Contribute to standardizing metrics, data definitions, and modeling patterns
- Contribute to P