Data Engineer - Credit Karma

Overview

Intuit Credit Karma is a mission-driven company focused on championing financial progress for our more than 130 million members globally. We offer free credit scores and a range of services to support financial goals, including identity monitoring, applying for credit cards, shopping for insurance and loans, and savings and checking accounts. Credit Karma has grown to more than 1,700 employees across 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 contributing to the broader infrastructure and services that enable reliable and efficient data processing and experiment execution s is an end-to-end engineering role with a strong emphasis on software engineering fundamentals, focusing on building scalable, maintainable systems and contributing 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.

• 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

• 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 both data and service-layer components of the data and experimentation platform

• Collaborate with engineers to improve platform capabilities, scalability, and developer experience

• Support systems that enable reliable experiment execution, metric computation, and analysis at scale

• Implement monitoring, alerting, and validation to ensure high data quality and system reliability

• Troubleshoot complex data and system issues, performing root cause analysis and driving resolution

• Continuously improve system performance, scalability, and cost efficiency

• Partner with Product Management, Data Architects, Data Scientists, Product Analysts, and Software Engineers to define and deliver data solutions

• Translate ambiguous requirements into scalable technical designs and drive execution end-to-end

• Bachelor’s degree in Computer Science, Engineering, or a related technical field

• 10+ years of experience in software engineering, data engineering, or a related role

• Strong programming skills in at least one language (e.g., Python, Java, Scala), with solid software engineering fundamentals

• Expertise in SQL and strong understanding of data modeling and data warehousing concepts

• Demonstrated success building and maintaining large-scale data pipelines using technologies such as Google Dataflow, Big Query, Airflow/Composer, Spark, or Flink

• Experience designing and building scalable data pipelines and distributed systems

• Deep understanding of software development lifecycle best practices, including agile methodologies

• Excellent communication, collaboration, and stakeholder management skills