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We are looking for a Senior Data Engineer with expertise in Python and Spark to contribute to building state-of-the-art data platforms on AWS. As part of this role, you'll be integral to designing, implementing and optimizing ETL workflows for our robust Lakehouse architecture in a hybrid and collaborative work environment.
Ideal candidates will have strong technical expertise, a proactive mindset for solving complex challenges and the ability to collaborate effectively in an agile team. This role also provides an opportunity for experienced Data Engineers to step into a leadership role while continuing hands-on work with cutting-edge technologies.
RESPONSIBILITIES
- Design, develop and maintain scalable ETL workflows and data pipelines using Python and Spark on AWS
- Implement data solutions leveraging AWS services such as EMR, AWS Glue, AWS Lambda, Athena, API Gateway and AWS Step Functions
- Collaborate with architects, product owners and team members to break down data engineering solutions into Epics and User Stories
- Lead the migration of existing data workflows to the Lakehouse architecture employing Iceberg capabilities
- Ensure reliability, performance and scalability across complex and high-volume data pipelines
- Create clear and concise documentation for solutions and development processes
- Mentor junior engineers and contribute to team development through knowledge sharing, technical leadership and coaching
- Communicate technical concepts effectively to both technical and business stakeholders
REQUIREMENTS
- Significant experience as a Senior Data Engineer designing and implementing robust data solutions
- Expertise in Python, PySpark and Spark, with a solid focus on ETL workflows and data processing practices
- Hands-on experience with AWS data services such as EMR, AWS Glue, AWS Lambda, Athena, API Gateway and AWS Step Functions
- Demonstrable knowledge of Lakehouse architecture and related data services (e.g., Apache Iceberg)
- Proven experience in data modeling for data platforms and preparing datasets for analytics
- Deep technical understanding of data engineering best practices and AWS data services
- Skilled in decomposing technical solutions into Epics/Stories to streamline development in an agile environment
- Strong background in code reviews, QA practices, testing automation and data validation workflows
- Ability to lead and mentor team members while contributing to technical strategy and execution
- A Bachelors degree in a relevant field or certifications (e.g., AWS Certified Solutions Architect, Certified Data Analytics)
WE OFFER
- 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, over 22,000 courses on LinkedIn 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