Senior​/Lead Data Engineer; Databricks, PySpark

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EPAM is seeking multiple Senior/Lead Data Engineers with expertise with Databricks and Py Spark to join our growing team in London. As part of our expansion into several large client accounts, we are looking for current hands-on coding professionals who are passionate about data engineering and eager to solve complex problems  this role, you will collaborate with diverse teams to build, optimise and maintain robust data and analytics solutions.

The role requires 3-4 days working on client site in central London.

Applicants must have the right to work in the UK, as we are unable to offer visa sponsorship for this role.

• Design, develop and maintain scalable data pipelines and ETL processes using PySpark and Databricks
• Work closely with data architects, data scientists and business analysts to transform requirements into technical solutions
• Implement data quality, reliability and performance improvements across large, complex datasets
• Collaborate with Dev Ops and Cloud teams to deploy and optimise data solutions in Azure (or other cloud platforms)
• Troubleshoot, optimise and refactor existing pipelines for performance and scalability
• Contribute to best practices, coding standards and technical documentation
• Mentor junior engineers and lead technical discussions within client and internal teams

• Bachelor's or Master's Degree in Computer Science, Engineering, Mathematics or related fields or relevant work experience
• Strong experience in data engineering, with recent hands-on coding as a core part of your daily role
• Expertise in PySpark for building high-performance, distributed data pipelines
• Expertise in Databricks for large-scale data engineering and analytics workloads
• Strong experience with cloud platforms (Azure preferred)
• Solid understanding of SQL and relational database concepts
• Experience with CI/CD, Git and modern Dev Ops practices for data solutions
• Strong problem-solving, communication and client-facing collaboration skills
• Exposure to machine learning or data science workflows is a plus but not required

• 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
• Cycle scheme, 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, over 22,000 courses on Linked In Learning Solutions and much more
• 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
• * All benefits and perks are subject to certain eligibility requirements