Intuit Credit Karma is looking to build a comprehensive data model for their Unified Customer Profile, a critical component of Intuit's competitive advantage, to support multiple use cases across different products or domains and influence company-wide data strategies.
Requirements
- 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
- Ability to architect and develop scalable data solutions, staying ahead of industry trends and integrating best practices in data engineering.
Responsibilities
- 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.
- 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.
- 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.
- Develop, maintain, and enforce data architecture standards, best practices, and design patterns to ensure consistency and quality across data capabilities.
- 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 pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts, ensuring efficient and effective data integration and processing.
- Mentor team members by giving/receiving actionable feedback, promoting growth and development.
Other
- Collaborate with stakeholders to understand the needs of capability customers, including data scientists, product managers, and business leaders.
- Influencing engineering, product and cross-functional teams to identify data opportunities and drive impactful business decisions.
- Excellent technical communication skills, with the ability to collaborate with cross-functional teams and drive technical innovation in data engineering.
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience with 10+ years of relevant experience.
- Strong background in data science, with experience identifying data gaps and inconsistencies, and communicating data warehouse plans to internal customers.
