Lead Data & AI Engineer

• 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

• 5+ 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 knowledge of CI/CD for data and ML pipelines (GitHub Actions, Azure DevOps) and experience with large-scale environments
• English proficiency at B2 level (Upper-Intermediate) or higher

Nice to have

• 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

• 26 paid holiday days
• Pension plan scheme
• Disability insurance (WGA Shortfall insurance)
• Long-term disability insurance (WIA Top up insurance)
• EPAM Employee Stock Purchase Plan (ESPP)
• Commuting to work - costs reimbursement
• Laptop + corporate simcard + corporate mobile device (subject to certain eligibility requirements)
• Bike lease
• Employee Assistance Program
• Corporate Programs including Employee Referral Program with rewards
• Learning and development opportunities including in-house training and coaching, professional certifications, and courses