Staff Data Engineer - Credit Karma

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.

Job Overview Come join Intuit's Consumer Group as a Staff Software Engineer - Data and help build Consumer Data Plane using Credit Karma and Turbotax Data to enable the data layer for AI-Native Experiences & Agents, Growth marketing, In-product personalization, Expert, 3rd Party surfaces, and Agentic Browsers.  The team owns the data platform at Credit Karma — from service emission to data lake landing to consumer hydration. We build the frameworks, pipelines, and persistence layers that every product team depends on to move data reliably at scale. Our systems ingest hundreds of terabytes per day across Kafka, Pub/Sub, and Dataflow, setup Data Governance, persist to Spanner and BigQuery, and serve low-latency reads to real-time product experiences through our Consumer Data Plane. This is a foundational engineering role — you will build the frameworks and infrastructure that other engineers across Credit Karma use to ship data-intensive features. If you care about developer experience, system reliability, and solving hard distributed systems problems at scale, this team is for you. Responsibilities Design, build, and maintain high-throughput, low-latency data frameworks used across Credit Karma's engineering organization, including ETL templates, persistence libraries, and streaming data pipelines Develop and extend Scala-based microservices and frameworks built on Finagle, Akka Streams, and gRPC that process petabytes of data daily Build and optimize cloud-native data pipelines on Google Cloud Platform using Dataflow (Apache Beam), Flink, Spark, Pub/Sub, BigQuery, and Spanner Own and evolve our Kafka-based streaming infrastructure — designing producers, consumers, and connectors that handle hundreds of terabytes of events per day with strict latency and durability guarantees Build persistence frameworks that provide a unified, type-safe API for reading and writing across Spanner, MySQL, and BigQuery Build agentic systems, semantic search, knowledge graph and personalization to disrupt how consumers do their taxes, money and personal finance using Consumer Data Plane Design and implement encryption, decryption, and fine-grained access control capabilities as reusable framework features, ensuring compliance with data governance requirements Create self-service developer tooling — CLI tools, templates, and onboarding automation — that reduces the time for other teams to adopt the