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Salary: USD 188,500 - 274,000 / annual
Intuit is seeking a Staff Data Engineer to join the Dev360 team, a critical initiative that provides comprehensive operational visibility across Intuit's applications and services. This role focuses on architecting and building fault-tolerant, scalable big-data platforms that support high-velocity, high-volume data use cases across the organization.
You will architect, design, and build scalable data platforms that enable Intuit's engineers and leaders to access operational data needed to understand product performance in real-world conditions. This includes tracking the entire software development lifecycle from code commits to customer adoption, and identifying improvement opportunities.
Key responsibilities include:
- Architecting fault-tolerant, scalable big-data platforms for high-velocity data use cases
- Collaborating cross-functionally with Product Management, Engineering, and Central Data Lake teams to ensure platform alignment and extensibility
- Developing scalable architectures for data normalization, lineage, governance, ontology, and discoverability across diverse systems and business units
- Enabling data and AI capabilities by curating datasets for advanced analytics, GenAI, and machine learning initiatives
- Executing code reviews, promoting best practices, and establishing processes for testing, CI/CD, performance testing, capacity planning, monitoring, and incident response
- Demonstrating technical leadership, mentoring junior engineers, and fostering a culture of continuous learning
Required qualifications include 8+ years in product analytics, web analytics, or similar domains; advanced SQL and big-data technology proficiency (Redshift, Spark, Hive, BigQuery); strong Python or Java/Scala skills; experience engineering data pipelines and workflow orchestration; understanding of AI-native and GenAI architectures; strong business acumen and data storytelling abilities; and excellent cross-functional collaboration skills. Bachelor's degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics, or related field required; Master's preferred.
