Senior Staff Software Engineer

Overview

Join Intuit’s Business Intelligence (BI) Platform team as we reimagine the next generation of scalable, intelligent data infrastructure. We serve over 240TB of data, 2 billion records daily, and deliver 200+ million report requests through 20+ complex pipelines—supporting enterprise and mid-market customers on their most critical decisions.

What youll bring

• 12–15 years of experience in data engineering with deep expertise in distributed, cloud-native systems.
• Proven experience designing and operating systems leveraging polyglot storage models (OLAP, NoSQL, key-value, etc.).
• Strong knowledge of OLTP and OLAP workloads, including best practices in bridging real-time and batch processing paradigms.
• Demonstrated success scaling platforms for high concurrency, large data volumes, and tight latency requirements.
• Expert in data modeling, schema evolution, and designing for resilience and extensibility.
• Strong working knowledge of AWS data services (Redshift, S3, Glue, Athena, EMR) and performance optimization.
• Experienced in planning and executing migration strategies and system deprecation in enterprise environments.
• Effective collaborator and communicator with a track record of influencing across product, data science, and engineering teams.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.Why
  
  

• Design and implement robust, scalable data pipelines optimized for low-latency and high-throughput use cases.
• Drive architecture decisions and evolve our platform toward polyglot persistence patterns, including RDBMS, NoSQL, key-value, time-series, and OLAP systems (e.g., Druid).
• Lead real-time data processing initiatives, including stream-based ingestion and transformation (e.g., with Kafka/Flink/Spark Streaming).
• Own data modeling strategies—normalized vs. denormalized schema design, schema evolution, and storage optimization.
• Scale our data layer to support large-scale multi-entity reporting and cloud-native architectures on AWS (e.g., Redshift, S3, Glue).
• Collaborate with engineering and product stakeholders to align platform capabilities with business needs and SLAs.
• Plan and execute migration strategies for legacy systems, ensuring a smooth path toward modernization and system deprecation.
• Enforce best practices across data governance, testing, CI/CD, and observability to maintain operational excellence.
• Contribute to internal tooling that boosts engineering productivity, visibility, and reliability of the data platform.