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Senior Manager, Data Engineering

Dropbox

LocationUnited States
SenioritySenior manager
CompanyDropbox
Verification agingOct 8
Compensation

$180k-$274k

Salary details are shown when available from the source listing. Sign in before applying so the role can be reviewed against your resume, salary goals, seniority, timezone, and location eligibility.

Requirements and working style

Decision details from the source listing

Experience

8+ years stated

Schedule

unspecified

These fields are normalized from the employer's text. Confirm details on the employer site before applying.

WFH.team analysis

What this posting tells you

Dropbox seeks a Senior Manager, Data Engineering to lead a team building and operating data pipelines, data products, and self-serve analytics foundations. Requires 8+ years in data engineering or backend/data infrastructure and 3+ years directly managing engineering teams. The role is remote in the US but limited to select locations; compensation range is $180,200–$274,300.

Role lane

Backend, Customer success, Data, Design and creative, DevOps, Finance and investments, Legal, Medical billing, Product, QA and testing, Software

Where you can work

United States

Working hours

Timezone overlap is not stated.

Arrangement

Senior manager · contract

Required signals
Data engineeringBackend or data infrastructureBatch and streaming pipelinesSparkdbtAirflow or orchestrationDatabricks, Snowflake, or BigQueryData modelingData quality and observabilityData lineageData SLAsIncident responseEngineering team management
Preferred signals
Self-serve data or analytics platformsAI coding tools or LLM-based engineering toolsCompute and storage cost optimizationData governance, privacy, and access controlPod or embedded operating model
Confirm before applying
  • Required timezone overlap is not stated
Market context

Backend hiring on WFH.team

4,932active related roles
1,461new in the latest period
202.7jobs per 100 candidates
$180kmedian of comparable listed ranges

This role's listed pay is above the median among 200 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.

Explore the remote job market
Skills and signals
Data engineeringBackend or data infrastructureBatch and streaming pipelinesSparkdbtAirflow or orchestrationDatabricks, Snowflake, or BigQueryData modelingData quality and observabilityData lineageData SLAsIncident responseEngineering team managementSelf-serve data or analytics platformsAI coding tools or LLM-based engineering toolsCompute and storage cost optimizationRemote - US, limited to select locations
Job description

Senior Manager, Data Engineering at Dropbox

Role Description

We are seeking a Senior Manager, Data Engineering to lead the team responsible for Dropbox’s underlying data foundations that power our business as a whole. 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 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

Company context

Working remotely at Dropbox

Dropbox is the world’s first smart workspace that helps people and teams focus on the work that matters.

Headquarters
United States, Australia, and Ireland
Team size
1001-5000
Founded
2007
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Remote Senior Manager, Data Engineering at Dropbox | WFH.team