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Senior Manager, Data Platform Enginering

Senior Manager, Data Platform Enginering

Procore Technologies
10-12 Years
Not Disclosed

This job is no longer accepting applications

Job Description

Job Ad

We're looking for a seasoned Senior Manager, Data Platform Engineering to join our Data Platform organization in Bengaluru, India. In this role, you will have the opportunity to shape the future of our data ecosystem by building the tools, frameworks, and policies that ensure our data is inventoried and handled responsibly, securely, and efficiently throughout its entire lifecycle.

As the Senior Manager, Data Platform Engineering, you will lead a high-performing team of engineers dedicated to creating a world-class governance layer. You will partner closely with stakeholders across the organization to balance data accessibility with rigorous protection standards. The ideal candidate is a technical leader who doesn't just manage governance but treats it as an engineering challenge, leveraging AI and automation to accelerate value delivery and simplify compliance.

This position reports to the Director of Data Platform. We're looking for someone to join our team immediately.

What you'll do:

  • Lead & Build: Oversee a dedicated engineering team responsible for the design, development, and maintenance of our data platform and lifecycle management backend services and infrastructure.
  • Architect Platform Services: Design and build the platform services, APIs, and infrastructure that automate data infrastructure policy enforcement, accurate metadata management, and comprehensive data security and access management at a global scale.
  • Drive AI Innovation: Proactively identify opportunities to use AI to automate manual governance processes, improve data quality, and accelerate developer throughput.
  • Engineer Data Lifecycle Systems: Engineer backend services and automated systems that execute data retention, archival, and deletion policies at scale to optimize performance and ensure global regulatory compliance.
  • Collaborate Strategically: Work alongside Product, Security, and Legal teams to translate complex global regulatory requirements and security policies into seamless technical solutions that support our broader data platform goals.
  • Software Excellence: Lead your team through all phases of the AI SDLC, ensuring high-quality, scalable, and maintainable code delivered in an iterative, agile fashion, largely driven by AI.
  • Mentor & Uplevel: Coach and support your engineers through regular feedback, career development planning, and technical mentorship, fostering a culture of excellence and high ownership.

What we're looking for:

  • Bachelor's Degree in Computer Science, Engineering, or a related field; Master's preferred.
  • 10+ years of experience in software engineering and data platform operations, with at least 3+ years in a leadership or people management role.
  • Proven expertise in building software platforms, including strong programming proficiency (e.g., Python, Go, or Java), alongside hands-on experience with modern data lakehouse architectures, streaming technologies (e.g., Kafka, Databricks), and various database technologies (Postgres, Redis, GraphDB, etc.).
  • Deep expertise in data platform security, implementing robust data policies, and engineering fine-grained access management solutions for globally distributed data environments.
  • Experience engineering custom, automated data platform solutions from the ground up, including metadata catalogs, enterprise-wide access control frameworks, and data lineage tools operating at a global scale.
  • Demonstrated ability to apply AI/LLM tools to automate engineering workflows or data management tasks.
  • Strong proficiency in cloud environments (AWS preferred) and infrastructure-as-code (Terraform).
  • Excellent communication skills with the ability to influence technical roadmaps and bridge the gap between technical execution and business policy.
  • A strong bias for action and a proven track record of delivering complex, distributed systems at scale.

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