Data Engineering Leader: Self-Serve Analytics & Reliability

Socket.dev; United States; On-site; USD 180,200 - 274,300; Full time

Job summary

Dropbox is seeking a Senior Manager, Data Engineering to lead the team responsible for the reliability, quality, cost, and velocity of the data platform. This hands-on engineering leader owns ingestion, transformation, orchestration, and serving layers, plus the self-serve analytics substrate used by partner teams.

The ideal candidate combines deep technical expertise with product-minded leadership, driving durable data products while mentoring engineers and partnering with Data Science, BI,

Qualifications

• 8+ years of data engineering or backend data infrastructure experience.
• 3+ years of direct people management and team design.
• Proven track record building and operating large-scale batch and streaming pipelines.
• Experience with lakehouse or warehouse stacks (Databricks, Snowflake, BigQuery).
• Strong collaboration and ability to align engineers, data science, analytics, and business partners.

Responsibilities

• Lead data engineering team responsible for reliability, quality, cost, and velocity of the data platform.
• Own ingestion, transformation, orchestration, and serving layers and the self-serve analytics substrate.
• Drive data quality, observability, lineage, and outcome-oriented metrics.
• Partner with Data Science, BI, Analytics, Product, Data Platform, and CTO org to define semantic layer and data contracts.
• Establish engineering practices including code review, testing, CI/CD, incident response, and postmortems; promote AI tooling.

Skills

Data leadership

Team management

Spark

dbt

Airflow

Databricks

Snowflake

BigQuery

Reliability

Tools

Airflow

dbt

Databricks

Snowflake

BigQuery

CI/CD

Job description

Dropbox is seeking a Senior Manager, Data Engineering to lead the team responsible for the reliability, quality, cost, and velocity of the data platform. This hands-on engineering leader owns ingestion, transformation, orchestration, and serving layers, plus the self-serve analytics substrate used by partner teams.

The ideal candidate combines deep technical expertise with product-minded leadership, driving durable data products while mentoring engineers and partnering with Data Science, BI,