Senior Data Engineer – Talent Analytics & Databricks

EY; Atlanta (GA); Hybrid; USD 85,000 - 159,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking a Data Engineering Senior Analyst to design, operate, and maintain data pipelines and analytics platforms, including Databricks, that support enterprise reporting, dashboards, and advanced analytics across the Talent ecosystem. This role collaborates with Talent Delivery, IMT, Digital Talent, and reporting teams to ensure data availability, integrity, security, and performance.

You will participate in UAT, validation, and post‑deployment support, while guiding data governance and

Qualifications

• Bachelor’s degree in data, technology, engineering, or related field.
• Hands-on experience with Databricks and data pipelines.
• Strong SQL skills and familiarity with ETL tools.
• Knowledge of HR data, reporting, and governance principles.
• Experience in analytics platforms and data security considerations.

Responsibilities

• Design, build, and maintain data pipelines and transformations.
• Develop and optimize Databricks notebooks and workflows.
• Ensure data reliability, security, and performance across environments.
• Collaborate with Talent Delivery, IMT, and reporting teams on data needs.
• Participate in UAT, deployments, and governance activities.

Skills

Databricks

SQL

Analytics platforms

HR data knowledge

Data security

Education

Bachelor's degree in data/technology/engineering

Master’s preferred

Tools

SSIS/SSMS

Job description

EY is seeking a Data Engineering Senior Analyst to design, operate, and maintain data pipelines and analytics platforms, including Databricks, that support enterprise reporting, dashboards, and advanced analytics across the Talent ecosystem. This role collaborates with Talent Delivery, IMT, Digital Talent, and reporting teams to ensure data availability, integrity, security, and performance.

You will participate in UAT, validation, and post‑deployment support, while guiding data governance and