Staff Data Engineer

Intuit Credit Karma is a mission-driven company, focused on championing financial progress for our more than 140 million members globally. While we're best known for pioneering free credit scores, our members turn to us for everything related to their financial goals, including identity monitoring, applying for credit cards, shopping for insurance and loans (car, home and personal) and savings accounts and checking accounts* – all for free. 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, Bangalore, and New York City.
*Banking services provided by MVB Bank, Inc., Member FDIC

About the team and the role: 

Intuit Credit Karma seeks a seasoned Staff Data Engineer to play a key role in building a comprehensive data model for our Unified Customer Profile, a critical component of Intuit's competitive advantage. With a strong background in data architecture and engineering, you will design and implement scalable data solutions that support multiple use cases across different products or domains. Your expertise will directly impact the direction of engineering teams and influence company-wide data strategies, fostering a culture of innovation and operational excellence. This role carries significant responsibility and visibility—as a Staff Engineer, you’ll be one of the most senior leaders shaping both the technical vision and the culture of our organization. You’ll set the tone, inspire the team, and be a driving force behind our success.

We seek engineers who act decisively and focus relentlessly on delivering practical solutions. If you’re ready to step up, lead with impact, and help define the future, this opportunity is yours.

What you’ll do:

• Develop and Conceptualize Data Architecture Capabilities: Design, develop, and own data architecture capabilities for large-scale projects, focusing on data ingestion, processing, storage, and retrieval, while evaluating design and operational cost-benefit tradeoffs within systems.
• Build Unified Customer Profile: Lead the development of a comprehensive data model and services for Credit Karma and Intuit's Unified Customer profile, integrating financial data across multiple sources and systems, ensuring data quality and governance.
• Understand Capability Customers: Collaborate with stakeholders to understand the needs of capability customers, including data scientists, product managers, and business leaders.
• Develop and Drive Data-Driven Roadmaps: Develop roadmaps for data architecture capabilities that align with business objectives and overall technology strategy, influencing engineering, product and cross-functional teams to identify data opportunities and drive impactful business decisions.
• Establish Data Architecture Best Practices: Develop, maintain, and enforce data architecture standards, best practices, and design patterns to ensure consistency and quality across data capabilities.
• Enable Seamless Data Integration and Interoperability: Foster data integration and interoperability across Credit Karma and Intuit's systems, enabling seamless data sharing and powering personalized member experiences by solving complex data integration problems using optimal ETL patterns, frameworks, and query techniques.
• Optimize Data Infrastructure for Efficiency: Optimize data pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts, ensuring efficient and effective data integration and processing.
• Mentor and Develop Team Members: Mentor team members by giving/receiving actionable feedback, promoting growth and development.

Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience with 10+ years of relevant experience.
• Deep understanding of data modeling principles, including schema design and dimensional data modeling, with experience in writing efficient SQL queries.
• Experience with data processing, storage, and querying technologies (e.g., Hadoop, Spark, Flink Streaming, Bigquery, Dataflow, Airflow, Bigtable, Spanner and Dynamo) and object-oriented programming languages (e.g., Python, Java, C++).
• Experience with semantic search (e.g Vertex AI search, AWS cloud search) and knowledge graph (e.g neo4j, ..) to integrate our data with generative AI experiences  
• Strong background in data science, with experience identifying data gaps and inconsistencies, and communicating data warehouse plans to internal customers.
• Ability to architect and deve