[Hiring] Lead Data Engineer @EPAM Systems

Role Description

We are looking for a Lead Data Engineer to build and evolve a next-generation analytics platform with a strong focus on Databricks and scalable data products. You will combine hands-on delivery with technical leadership across ingestion, modeling, governance, and AI-enabled engineering practices.

• Design scalable data ingestion, transformation, and data product frameworks
• Define Databricks best practices, including Medallion Architecture, optimization, governance, and operational standards
• Build batch, near real-time, and streaming pipelines using Databricks capabilities
• Deliver end-to-end data products that support analytics use cases across domains
• Develop trusted analytical datasets, semantic models, and governed consumption layers for reporting
• Implement data quality, lineage, monitoring, and observability practices across pipelines
• Enable self-service analytics through reusable, business-ready datasets and platform features
• Lead proof-of-concepts and evaluate emerging capabilities across the Databricks ecosystem
• Define AI SDLC practices and AI-assisted development patterns to accelerate delivery
• Partner with engineering, analytics, product, and business stakeholders and mentor engineers on best practices

Qualifications

• 5+ years of data engineering experience
• 1+ years of technical leadership experience guiding engineering standards and best practices
• Strong platform delivery experience building enterprise analytics solutions end to end
• Advanced Apache Spark and PySpark expertise for large-scale processing
• Strong Databricks production experience with performance optimization and operational excellence
• Advanced SQL skills for transformation, modeling, and analytics consumption
• Strong data governance knowledge including security, quality, and lineage practices
• Solid CI/CD experience and Data Engineering SDLC best practices
• Strong communication skills to lead technical discussions with cross-functional stakeholders
• Upper-Intermediate English proficiency (B2) for day-to-day collaboration

Requirements

• Data Architecture experience designing lakehouse patterns and enterprise data platforms (Nice to have)
• Data Solution Architecture experience translating analytics needs into scalable designs (Nice to have)
• Scala proficiency for Spark-based development and optimization (Nice to have)