Lead Data Engineer – Analytics Platform

About the role

EPAM is seeking a Lead Data Engineer to design and evolve a next‑generation analytics platform focused on Databricks and scalable data products. The role blends hands‑on delivery with technical leadership across data ingestion, modeling, governance, and AI‑enabled engineering practices.

Key responsibilities

• Design scalable data ingestion, transformation, and product frameworks using Databricks.
• Define Databricks best practices, including Medallion Architecture, optimization, governance, and operational standards.
• Build batch, near‑real‑time, and streaming pipelines and deliver end‑to‑end data products for analytics use cases.
• Develop trusted analytical datasets, semantic models, and governed consumption layers for reporting.
• Implement data quality, lineage, monitoring, and observability across pipelines.
• Lead proof‑of‑concepts and evaluate emerging Databricks ecosystem capabilities.

Required profile

• 5+ years of data engineering experience with strong platform delivery background.
• 1+ years of technical leadership guiding engineering standards and best practices.
• Upper‑Intermediate English proficiency (B2) for day‑to‑day collaboration.

Required skills

• Advanced Apache Spark and PySpark expertise for large‑scale processing.
• Strong Databricks production experience with performance optimization.
• Advanced SQL skills for transformation, modeling, and analytics consumption.
• Solid CI/CD experience and data‑engineering SDLC best practices.
• Data governance knowledge including security, quality, and lineage.

What we offer

• International projects with top brands and global career opportunities.
• Healthcare benefits, employee financial programs, paid time off and sick leave.
• Upskilling, reskilling and certification courses with unlimited LinkedIn Learning access.
• A supportive culture recognized by Glassdoor, Newsweek and LinkedIn.