We are looking for a highly skilled Senior Data Engineer to join a team responsible for the development, maintenance, and evolution of the data platforms that power a specialized clinical trial management application. This role calls for a technically experienced professional who can work autonomously to design, build, optimize, and support modern data pipelines, ensuring the quality, reliability, and availability of information for critical analytical and operational processes.
Responsibilities
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Design, develop, and maintain scalable and reliable data pipelines for data ingestion, transformation, and consumption
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Build ETL/ELT processes using modern data engineering technologies
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Develop and optimize data transformations using Python, PySpark, and dbt
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Design and manage data storage and processing solutions in Snowflake
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Apply best practices in data modeling, data architecture, and information governance
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Contribute to support, monitoring, and incident resolution activities related to data integration processes and data platforms
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Define automation, testing, and deployment strategies through CI/CD practices
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Collaborate with cross-functional teams across development, product, analytics, and business to understand requirements and translate them into efficient technical solutions
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Ensure data quality, consistency, and traceability throughout the entire information lifecycle
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Identify opportunities to improve the performance, scalability, security, and maintainability of data solutions
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Document architectures, technical processes, and development standards
Requirements
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3+ years of experience in Data Engineering
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Strong development experience with Python
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Advanced experience with PySpark for distributed data processing
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Hands-on experience with Snowflake (modeling, optimization, development, and administration of data objects)
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Experience implementing transformations using dbt (Data Build Tool)
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Knowledge and practical experience applying CI/CD practices for data solutions
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Solid command of the following concepts: Data Modeling, Data Warehousing, Data Lake / Lakehouse, Data Architecture, Data Integration and Orchestration
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Experience with version control using Git
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Ability to design technical solutions independently and lead complex data engineering initiatives
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Strong analytical and problem-solving skills
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Self-driven, results-oriented approach
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Effective communication with both technical and functional teams
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Ability to manage multiple priorities simultaneously
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Architectural mindset with a focus on scalability
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Proactivity in identifying risks and improvement opportunities
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Attention to detail and commitment to quality
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Strong English communication skills (B2 level or higher)
Nice to have
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Experience with cloud environments (AWS, Azure, or GCP)
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Familiarity with orchestration tools such as Airflow or similar
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Experience working in regulated environments, preferably in healthcare, pharmaceutical, or clinical research sectors
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Knowledge of data quality and pipeline observability
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Experience with Agile/Scrum methodologies
We offer
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International projects with top brands
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Work with global teams of highly skilled, diverse peers
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Healthcare benefits
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Employee financial programs
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Paid time off and sick leave
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Upskilling, reskilling and certification courses
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Unlimited access to the LinkedIn Learning library and 22,000+ courses
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Global career opportunities
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Volunteer and community involvement opportunities
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EPAM Employee Groups
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Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn
EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.
