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Staff Software Engineer, Lakehouse Data Platform

Procore

Procore

Software Engineering
Bengaluru, Karnataka, India
Posted on Mar 11, 2026
Job Ad

We're looking for a Staff Software Engineer to join Procore's Product & Technology Team. Procore software solutions aim to improve the lives of everyone in construction and the people within Product & Technology are the driving force behind our innovative, top-rated global platform. We're a customer-centric group that encompasses engineering, product, product design and data, security and business systems.

You'll be the technical lead for a growing team of engineers in India that owns Procore's lakehouse data platform, the storage, compute, and catalog infrastructure that powers analytics, data products, and AI across the company. This is not a people management role (the team reports to a Senior Engineering Manager in the US), but you'll be the most senior technical voice on the ground, responsible for driving engineering quality, making day-to-day technical decisions, and helping the team move with confidence and autonomy. If you're energized by both writing great code and raising the engineers around you, this role is for you.

This role reports to a US-based Senior Engineering Manager and is based in Bengaluru, India.

What you'll do:

  • Serve as the technical lead for engineers in India, providing technical direction and architectural guidance as part of a distributed data platform team.
  • Operate effectively across time zones, maintaining strong async communication and ensuring teammates in India are unblocked and aligned.
  • Contribute to the technical roadmap for Procore's lakehouse data platform in partnership with engineering leadership, helping shape decisions that balance velocity, reliability, and cost-efficiency.
  • Lead development of internal tools, automation frameworks, and self-service capabilities that improve developer productivity and move the team toward a more scalable lakehouse platform.
  • Drive platform engineering work across the lakehouse stack, including table format management, catalog and access control, cluster lifecycle automation, storage optimization, and data quality infrastructure.
  • Use AI-assisted development and modern engineering practices to accelerate delivery, raise the quality bar, and set the standard for how the team uses AI tools effectively.
  • Establish and enforce software engineering standards (code quality, testing strategies, observability patterns, API design), and provide technical mentorship through system design reviews, code reviews, and hands-on troubleshooting of complex production issues.
  • Lead incident response efforts and participate in on-call rotations, while building systems and automation that minimize manual intervention over time.

What we're looking for:

  • Proven technical leadership experience, having served as a tech lead or senior technical contributor on an engineering team, with a track record of elevating the engineers around you.
  • Strong async and cross-timezone communication skills, with experience operating autonomously and keeping distributed teams aligned.
  • A builder's mindset. You want to engineer the systems that power the data platform, not run queries on top of them. Experience with lakehouse technologies (e.g., Databricks, Delta Lake, Unity Catalog, Apache Iceberg) is strongly preferred.
  • 8+ years of professional experience in software engineering. Experience in platform engineering, infrastructure software, or building internal developer tools is preferred.
  • A genuine interest in AI-assisted development and demonstrated experience using AI tools to increase personal and team engineering velocity.
  • Strong software engineering fundamentals and expert-level coding skills in modern languages (e.g., Python, Scala, Java), including system design, clean code practices, testing strategies, and experience building and operating production-grade services.
  • Deep understanding of cloud platforms (AWS, Azure, or GCP) including compute, storage, networking, and managed service offerings for data workloads.