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.
Responsibilities
- 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
Requirements
- 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
Nice to have
- Data Architecture experience designing lakehouse patterns and enterprise data platforms
- Data Solution Architecture experience translating analytics needs into scalable designs
- Scala proficiency for Spark-based development and optimization
We offer
- International projects with top brands
- Work with global teams of highly skilled, diverse peers
- Healthcare benefits
- Employee financial programs
- Paid time off and sick leave
- Upskilling, reskilling and certification courses
- Unlimited access to the LinkedIn Learning library and 22,000+ courses
- Global career opportunities
- Volunteer and community involvement opportunities
- EPAM Employee Groups
- Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn
EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.
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