Jobs › Senior Manager, Data Engineering & Governance
Senior Manager, Data Engineering & Governance
Job at a glance
- Category
- Data Governance
- Work arrangement
- Remote
- Location
- Seattle, WA
- Posted
- Jul 31, 2026
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Dropbox is hiring a Senior Manager, Data Engineering & Governance in Seattle, WA. This is a Data Governance job in the governance, risk, and compliance field. Review the full details below and apply directly with Dropbox.
Role Description We are seeking a Senior Manager, Data Engineering to lead the team responsible for the reliability, quality, cost, and velocity of Dropbox's core data platform. This is a hands-on engineering leader who owns the pipelines and data products that Product, GTM, Finance, and the CTO organization depend on to make decisions. In this role, you will lead and grow a team of data engineers building and operating our ingestion, transformation, orchestration, and serving layers, as well as the self-serve analytics substrate that lets partner teams answer their own questions without bespoke engineering work. The ideal candidate is a deeply technical, product-minded engineering leader who can hold a high bar on system reliability and data quality while partnering closely with Data Science, Business Intelligence Engineering, Analytics, and Product to turn fragmented, ticket-driven data work into durable, reusable data products. Responsibilities Data Quality & Observability: Establish and enforce a rigorous data quality culture: lineage, freshness monitoring, anomaly detection, and outcome-oriented, gaming-resistant quality metrics. Self-Serve Platform: Lead the engineering of the self-serve analytics substrate, reducing bespoke request volume and increasing partner-team autonomy. Cost & Efficiency: Own the unit economics of the data platform, compute and storage efficiency, and drive measurable improvements without sacrificing reliability. Cross-Functional Partnership: Partner deeply with Data Science, BIE, Analytics, Product, Data Platform, and the CTO org to define the semantic layer, modeling standards, and data contracts that make downstream work trustworthy and fast. Engineering Culture: Establish rigorous engineering practices, code review, testing, CI/CD for data, incident response, and postmortems, and champion the effective, measured use of AI coding tools to improve engineering productivity. Team Leadership: Lead, mentor, and grow a high-talent-density team of data engineers, fostering a culture of ownership, technical excellence, psychological safety, and continuous learning. Requirements 8+ years of data engineering or backend/data infrastructure experience with increasing scope, ideally in high-scale environments. 3+ years of experience directly managing and growing engineering teams, including hiring, coaching, performance management, and team design. Deep Technical Expertise: Proven track record building and operating large-scale batch
Full responsibilities and requirements are on Dropbox's application page.
Apply for this job →Location and market context
This is a remote data governance job, so it draws from a national talent pool rather than a single metro. Remote governance and compliance jobs reward candidates who can show they work effectively across time zones and distributed legal, security, and product teams. Confirm any residency, travel, or occasional-onsite expectations directly with Dropbox.
About data governance jobs
Data governance establishes ownership, quality, and controls over data as an asset. It is foundational to trustworthy analytics and AI, spanning cataloging, lineage, and access. Jobs like this one are typically evaluated against frameworks such as data management frameworks, data quality and lineage standards, and privacy and security controls.
How to position yourself for this data governance job
Strong candidates emphasize data ownership and stewardship, quality and lineage, catalog and access controls, and enabling analytics and AI on a trusted data foundation. In your resume and outreach, tie your experience to how Dropbox would apply data management frameworks, data quality and lineage standards, and privacy and security controls, and lead with concrete outcomes rather than duties.
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