Lead the org-wide data platform that powers every product and AI workflow across the company
Job Summary
Lead the org-wide data platform that powers every product and AI workflow across the company.
Build, mentor, and grow high-performing distributed engineering teams that thrive in a culture of autonomy, ownership, and operational excellence.
Shape technical strategy for distributed systems, streaming infrastructure, lakehouse, and Knowledge Platform, making high-impact architectural decisions affecting all products, AI workflows, and business-critical processes.
Matching Summary
Lead the org-wide data platform that powers every product and AI workflow across the company.
Skills & Requirements
Must-have
Data Platform Architecture
Streaming / Event Processing
Lakehouse Platforms
Knowledge / Semi-structured Data Platform
Distributed Data Processing
Platform Reliability & Monitoring
Schema Governance & Validation
AWS Cloud Infrastructure
Python & SQL
Engineering Team Leadership
CI/CD and modern engineering practices
Nice-to-have
Experience supporting AI / ML workloads
Data governance and cataloging platforms
Internal developer platforms or APIs
Key Requirements
12+ years in software or data engineering
4+ years leading distributed engineering teams
Proven experience building high-performing, autonomous engineering cultures
Hands-on experience designing and operating large-scale data platforms
Familiarity with Databricks, Snowflake, or similar cloud data platforms
Strong understanding of distributed data processing, storage, and querying
Proven experience in platform reliability, monitoring, incident management, and operational excellence
Experience defining, enforcing, and monitoring schema governance, data quality, security, and compliance standards
Ability to balance cost, performance, reliability, and operational health
Strong programming skills in Python and SQL
Experience building tools and APIs for internal engineering teams
Ability to guide architectural decisions and design reviews
Comfortable partnering with multiple engineering teams and stakeholders in a remote-first, distributed environment