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Senior Manager, Data Engineering

Dropbox3h ago
United StatesRemoteFull-timeSenior Level8+ yrs exp
Visa-friendly

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Senior Engineering ManagerEngineering ManagerVp EngineeringVp DataSenior Data Engineer
  • Role Description
  • We are seeking a Senior Manager, Data Engineering to lead the team responsible for the reliability, quality, cost
  • 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
  • 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
  • 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
  • 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
  • the CTO org to define the semantic layer, modeling standards
  • data contracts that make downstream work trustworthy and fast.
  • Engineering Culture: Establish rigorous engineering practices — code review, testing, CI/CD for data, incident response
  • 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 and streaming pipelines (e.g., Spark, dbt, Airflow/orchestration) on a modern lakehouse or warehouse stack (e.g., Databricks, Snowflake, BigQuery).
  • Reliability & Quality: Demonstrated ownership of data SLAs, observability, lineage, and incident response for business-critical pipelines.
  • Systems & Modeling: Strong data modeling fundamentals and the ability to design a semantic layer and data contracts that serve many downstream consumers.
  • Stakeholder Management: Excellent communication and the ability to align engineering, data science, analytics, and business partners around shared reliability and quality goals.
  • Preferred Qualifications
  • Platform / Self-Serve Experience: Track record building self-serve data or analytics platforms that reduced bespoke request volume and increased partner autonomy.
  • AI-Forward Engineering: Experience integrating AI coding tools and LLM-based tooling into the engineering workflow, with a measured approach to impact and guardrails.
  • Cost Discipline: Demonstrated success improving compute/storage unit economics without regressing reliability.
  • Familiarity with modern data governance, privacy, and access-control practices.
  • Experience operating in a pod or embedded model serving multiple business partners.
  • Durable Skills
  • AI fluency means using these tools to amplify human judgment, not replace it. We believe people with these skills will thrive as work and technology continue to evolve:
  • Awareness: U nderstand yourself and others .
  • Judgment: E valuat e information and mak e decisions in complex situations .
  • Adaptability: L earn, adjust, and stay effective through change .
  • Connection: C ommunicat e , collaborat e , and build trust .
  • To learn more about why these skills matter and what the data shows about thriving through change, read this blog post from our Chief People Officer, Melanie Rosenwasser.
  • Compensation
  • US Zone 1
  • This role is not available in Zone 1
  • US Zone 2
  • $202,700 — $274,300 USD
  • US Zone 3
  • $180,200 — $243,800 USD

Required skills

Data EngineeringBackendData InfrastructureSparkdbtAirflowDatabricksSnowflakeBigQuery
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