About this role
Lead Dropbox's core data platform team, owning pipelines and data products that power decisions across Product, GTM, Finance, and CTO orgs. Build and operate ingestion, transformation, orchestration, and serving layers while enabling self-serve analytics for partner teams.
Must have
8+ years of data engineering or backend/data infrastructure experience with increasing scope in high-scale environments
3+ years directly managing and growing engineering teams including hiring coaching and performance management
Proven track record building and operating large-scale batch and streaming pipelines on modern lakehouse or warehouse stacks
Demonstrated ownership of data SLAs observability lineage and incident response for business-critical pipelines
Strong data modeling fundamentals and ability to design semantic layers and data contracts for downstream consumers
Excellent communication skills to align engineering data science analytics and business partners around shared goals
Technologies
Responsibilities
Establish and enforce rigorous data quality culture including lineage freshness monitoring anomaly detection and gaming-resistant metrics
Lead engineering of self-serve analytics substrate reducing bespoke request volume and increasing partner-team autonomy
Own unit economics of data platform including compute and storage efficiency and drive measurable improvements
Partner deeply with Data Science BIE Analytics Product and CTO org to define semantic layer modeling standards and data contracts
Establish rigorous engineering practices including code review testing CI/CD for data incident response and postmortems
Lead mentor and grow high-talent-density team of data engineers fostering ownership technical excellence and continuous learning
Benefits
Recruitment process
Role is hands-on engineering leader who owns pipelines and data products that Product GTM Finance and CTO organization depend on
Team builds and operates ingestion transformation orchestration and serving layers as well as self-serve analytics substrate
Ideal candidate is deeply technical product-minded engineering leader who can hold high bar on system reliability and data quality
Engineering Career Framework is publicly viewable describing expectations for engineers at each career level
Company emphasizes AI fluency as durable skill using tools to amplify human judgment not replace it
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