Senior Data Engineering Lead - Self-Serve Platform (Remote)

Namely; 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 our core data platform. This is a hands-on engineering leadership role owning pipelines and data products used by Product, GTM, Finance, and the CTO to make decisions.

You will lead data engineers across ingestion, transformation, orchestration, and serving layers, as well as the self-serve analytics substrate enabling partner teams to answer questions without

Qualifications

• Minimum 8+ years in data engineering with increasing scope and impact.
• At least 3+ years directly managing and growing engineering teams, including hiring and performance management.
• Proven experience building and operating large-scale batch and streaming pipelines using Spark, Airflow, dbt on modern lakehouse/warehouse stacks.

Responsibilities

• Lead the data engineering team to deliver reliable, high-quality data pipelines and products.
• Own ingestion, transformation, orchestration, and serving layers, plus self-serve analytics substrate.
• Drive cost efficiency while maintaining reliability and data quality.
• Partner with Data Science, Analytics, Product, and CTO to define data contracts and semantic layer.
• Establish engineering practices: code reviews, testing, CI/CD, incident postmortems, and AI-tool governance.
• Mentor and grow a high-talent team and foster ownership and continuous learning.

Skills

8+ years data engineering experience

3+ years people management

Spark

Airflow

dbt

Databricks

Snowflake

BigQuery

Data lakehouse

Tools

Spark

Airflow

dbt

Databricks

Snowflake

BigQuery

Job description

Dropbox is seeking a Senior Manager, Data Engineering to lead the team responsible for the reliability, quality, cost, and velocity of our core data platform. This is a hands-on engineering leadership role owning pipelines and data products used by Product, GTM, Finance, and the CTO to make decisions.

You will lead data engineers across ingestion, transformation, orchestration, and serving layers, as well as the self-serve analytics substrate enabling partner teams to answer questions without