Lead Data & AI Engineer

• Minimum 8+ years working in data engineering, with proven architecture and leadership experience
• Advanced proficiency in SQL for performance tuning at large scale
• Strong programming skills in Python, with applied experience in data engineering workflows
• Expertise in PySpark for distributed data processing
• Hands-on experience with Databricks, including Delta Lake and performance optimization
• Knowledge of Azure Data Factory for orchestration of pipelines (ETL/ELT)
• Familiarity with AI/ML pipeline development, including integration of models into production
• Demonstrated exposure to Gen AI-assisted development workflows for accelerating data engineering tasks
• Strong understanding of CI/CD processes for data and ML pipelines such as GitHub Actions, Azure DevOps
• Ability to manage enterprise-scale solutions across global environments with compliance in mind

• EPAM Employee Stock Purchase Plan (ESPP)
• Protection benefits including life assurance, income protection and critical illness cover
• Private medical insurance and dental care
• Employee Assistance Program
• Competitive group pension plan
• Cyclescheme, Techscheme and season ticket loans
• Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
• Learning and development opportunities including in-house training and coaching, professional certifications, and courses
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program

We're looking for a Lead Data & AI Engineer to join our team in the UK in a hybrid working mode. In this role, you will design and deliver advanced data solutions and AI-assisted capabilities on modern cloud platforms. You'll build scalable data pipelines, optimize data quality and governance and enable ML feature engineering for analytics and intelligent applications. The role requires hands-on technical expertise in data engineering and AI integration while driving reliability, performance and security for enterprise-scale systems.

Responsibilities

• Design and implement robust data architectures using cloud-native technologies
• Build large-scale ETL/ELT workflows to process heterogeneous datasets
• Create data models optimized for AI/ML pipelines and advanced analytics
• Develop streaming and batch pipelines leveraging tools like Azure Data Factory and Databricks
• Operationalize ML solutions, integrating feature stores, model registries and inference endpoints
• Collaborate with data scientists to deploy and monitor AI models using enterprise MLOps frameworks
• Integrate GenAI-assisted development methods into data workflows for automation and efficiency
• Ensure data governance, lineage, cataloging and quality frameworks across platforms
• Optimize platform performance, manage compute cost efficiency and enable observability for critical workloads
• Contribute to best practices, mentoring engineering teams in advanced data and AI engineering

Requirements

• Minimum 8+ years working in data engineering, with proven architecture and leadership experience
• Advanced proficiency in SQL for performance tuning at large scale
• Strong programming skills in Python, with applied experience in data engineering workflows
• Expertise in PySpark for distributed data processing
• Hands-on experience with Databricks, including Delta Lake and performance optimization
• Knowledge of Azure Data Factory for orchestration of pipelines (ETL/ELT)
• Familiarity with AI/ML pipeline development, including integration of models into production
• Demonstrated exposure to Gen AI-assisted development workflows for accelerating data engineering tasks
• Strong understanding of CI/CD processes for data and ML pipelines such as GitHub Actions, Azure DevOps
• Ability to manage enterprise-scale solutions across global environments with compliance in mind

Nice to have

• Experience in commodity trading and supply operations, ideally within the energy sector
• Prompt Engineering knowledge and experience building RAG workflows
• Familiarity with Microsoft Foundry platforms
• Version control and CI/CD experience with GitHub
• Understanding of ETL/ELT optimization patterns beyond Azure stack
• Knowledge of data mesh or lakehouse architectural concepts
• Hands-on exposure to dbt (data build tool), MKDocs and similar developer productivity tooling

Benefits

• EPAM Employee Stock Purchase Plan (ESPP)
• Protection benefits including life assurance, income protection and critical illness cover
• Private medical insurance and dental care
• Employee Assistance Program
• Competitive group pension plan
• Cyclescheme, Techscheme and season ticket loans
• Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
• Learning and development opportunities including in-house training and coaching, professional certifications, and courses
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program