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
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