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Senior Manager, Data Engineering

DropboxCloud Storage company
Remote$180,200 - $274,300 USDManager
Y Combinator logo
Y Combinator
Sequoia Capital logo
Sequoia Capital
Accel logo
Accel
Index Ventures logo
Index Ventures
Benchmark Capital
Greylock Partners logo
Greylock Partners
Data & AI

About the role

TL;DR

Senior Manager, Data Engineering to lead the core data platform team at Dropbox.

  • 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.
  • Key Responsibilities Establish and enforce a rigorous data quality culture: lineage, freshness monitoring, anomaly detection, and outcome-oriented, gaming-resistant quality metrics.
  • Lead the engineering of the self-serve analytics substrate, reducing bespoke request volume and increasing partner-team autonomy.
  • Own the unit economics of the data platform
  • compute and storage efficiency
  • and drive measurable improvements without sacrificing reliability.
  • Partner deeply with Data Science, BIE, Analytics, Product, Data Platform, and the CTO org to define the semantic layer, modeling standards, and data contracts.
  • 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 in building and operating large-scale batch and streaming pipelines (e.g., Spark, dbt, Airflow) on a modern lakehouse or warehouse stack (e.g., Databricks, Snowflake, BigQuery).
  • Demonstrated ownership of data SLAs, observability, lineage, and incident response for business-critical pipelines.
  • Strong data modeling fundamentals and the ability to design a semantic layer and data contracts that serve many downstream consumers.
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Required skills

SparkdbtAirflowDatabricksSnowflakeBigQuerySQLEngineering Management

Nice-to-have skills

PythonLLMs

Tech stack

PythonSparkdbtAirflowDatabricksSnowflakeBigQuerySQL

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