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Intuit Senior Staff Software Engineer 
India, Karnataka, Bengaluru 
243571972

05.09.2025
Responsibilities

  • 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.

Qualifications

  • 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