Databricks Data Engineering Manager - Analytics Leader

EY; Baltimore (MD); Remote; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking a dynamic Manager of Data Engineering to lead our team in building scalable cloud analytics solutions using Databricks across AWS, Azure, and GCP. You will mentor a growing team, engage with clients, and drive end-to-end data pipelines that deliver real business value.

The role requires strong technical leadership, data governance, and the ability to translate business needs into technical solutions while managing resources and budgets. Travel to client sites may be required.

Qualifications

• Bachelor’s degree in a related field required; Master’s preferred.
• Typically, 4–6 years of relevant experience in data engineering with cloud data solutions and analytics.
• Proven expertise in Databricks and experience with Spark for big data processing.
• Hands-on experience with AI-native data engineering practices to accelerate development and optimization.
• Strong programming skills in Python, Scala, or SQL.
• Experience leading and mentoring teams and managing client relationships.

Responsibilities

• Lead workstream delivery and ensure quality in all processes.
• Engage with clients daily, participate in working sessions, and identify opportunities for additional services.
• Implement resource plans and budgets while managing engagement economics.
• Guide the design and development of scalable data engineering solutions on Databricks across cloud platforms.

Skills

Databricks

Cloud analytics

Leadership

Client management

Python Scala SQL

AI data engineering

Education

Bachelor's degree

Master's preferred

Tools

Spark

GitHub Copilot

Cursor

Databricks Assistant

Job description

EY is seeking a dynamic Manager of Data Engineering to lead our team in building scalable cloud analytics solutions using Databricks across AWS, Azure, and GCP. You will mentor a growing team, engage with clients, and drive end-to-end data pipelines that deliver real business value.

The role requires strong technical leadership, data governance, and the ability to translate business needs into technical solutions while managing resources and budgets. Travel to client sites may be required.