Senior Manager, Data Engineering

Dropbox

Senior Manager, Data Engineering at Dropbox managing core data platform and leading engineering teams. Focus on data quality, self-serve analytics, and cross-functional partnerships.

Posted 7/29/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $202,700 - $274,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering, focusing on building and operating large-scale batch and streaming pipelines while ensuring data quality and reliability. Proven ability to lead and mentor engineering teams, fostering a culture of technical excellence and collaboration across cross-functional partnerships.

Highest-signal resume keywords

Data EngineeringTeam LeadershipData Quality & ObservabilityBatch & Streaming PipelinesStakeholder Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ModelingPipeline DevelopmentAnomaly DetectionData LineageCI/CD for DataIncident ResponseQuality MetricsPerformance ManagementTechnical Excellence

Soft Skills

CommunicationMentoringCollaborationPsychological SafetyContinuous Learning

Tools & Technologies

SparkDbtAirflowDatabricksSnowflakeBigQuery

Industry Keywords

Data InfrastructureSelf-Serve AnalyticsUnit EconomicsCross-Functional PartnershipEngineering Practices

Tech Stack

Tools & technologies

AirflowBigQuerySpark

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

This role is not available in Zone 1
US Zone 2: $202,700 - $274,300 USD
US Zone 3: $180,200 - $243,800 USD