Lead Data Engineer
We are looking for a Lead Data Engineer who has demonstrated skills in Azure Data Platform technologies, Databricks, and PySpark to join our expanding data engineering team. In this role, you will build and deliver scalable, cloud-native data solutions that support enterprise analytics, reporting, and business intelligence initiatives. You will handle large-scale datasets, build reusable ingestion frameworks, improve data pipelines, and contribute significantly to the development of modern data platforms built on Azure and Databricks. The ideal candidate combines solid hands-on technical skills with experience designing robust, metadata-driven data solutions, as well as a true passion for delivering high-quality, maintainable data products.
Responsibilities
- Design, build, and maintain scalable data ingestion, transformation, and delivery pipelines
- Deliver cloud-native data solutions leveraging Azure and Databricks technologies
- Develop and improve ETL/ELT processes using PySpark, Spark SQL, and Delta Lake
- Implement metadata-driven and configuration-based ingestion frameworks to enhance scalability and maintainability
- Develop and maintain batch and incremental data processing pipelines
- Establish data quality controls, validation frameworks, monitoring, logging, and error handling mechanisms
- Collaborate with business stakeholders, architects, and engineering teams to gather requirements and deliver data solutions
- Resolve production issues and drive continuous improvements in platform reliability and performance
- Monitor and optimize Databricks workloads for efficiency, scalability, and cost management
- Maintain engineering best practices including code reviews, automated testing, CI/CD, and infrastructure automation
- Support data governance, security, and access management efforts using Unity Catalog and Azure services
- Mentor team members and help define engineering standards and best practices
Requirements
- 5+ years of experience in Data Engineering or Software Engineering
- 1+ years of relevant leadership experience
- Strong skills in Azure Databricks, Apache Spark, and PySpark
- Proficient in Spark SQL with demonstrated experience building solutions on Azure cloud platforms
- Advanced Python programming abilities combined with strong SQL development and optimization experience
- Experience with Unity Catalog and enterprise data governance practices
- Familiarity with Git-based source control workflows
- Experience designing and maintaining CI/CD pipelines
- Understanding of orchestration tools such as Databricks Workflows and Azure Data Factory (ADF)
- Strong analytical, troubleshooting, and problem-solving abilities
- Excellent communication and stakeholder management skills
- English proficiency at B2 level or higher
Nice to have
- Understanding of Terraform and Infrastructure as Code (IaC)
- Experience with Databricks Asset Bundles
- Ability to build reusable data engineering frameworks and accelerators
- Strong skills in advanced Spark performance tuning and optimization
- Familiarity with enterprise-scale lakehouse architectures
- Experience with data security, compliance, and governance initiatives
- Experience working within Agile delivery teams
Benefits
- 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