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 pipelinessupporting enterprise and mid-market customers on their most critical decisions.
What you'll bring
- 1215 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
How you will lead
- 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 strategiesnormalized 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.
