Data Engineer

EPAM is a global provider of digital engineering, cloud, and AI-enabled transformation services, as well as a leading business and experience consulting partner.

• Architect, build and optimize scalable data pipelines for batch and real-time data processing;
• Develop and implement ETL/ELT workflows, ensuring efficient data ingestion, transformation and storage;
• Leverage modeling methodologies to enable scalable and flexible data modeling;
• Ensure data consistency, reliability and governance across data lakes, warehouses and operational data stores;
• Optimize performance and cost efficiency of data infrastructure on Azure;
• Implement and manage big data processing frameworks, such as Databricks and Kafka;
• Enhance data security and compliance, integrating RBAC, ABAC, encryption and regulatory frameworks into data infrastructure;
• Develop automation tools for data pipeline orchestration;
• Monitor, troubleshoot and optimize data pipelines;
• Collaborate with federated engineering teams to align data architecture with business and engineering goals;
• Provide clean, reliable and scalable datasets for advanced analytics and machine learning;
• Evaluate and adopt emerging technologies;
• Mentor and guide junior engineers.

• 5+ Years of experience in data engineering, ETL development or big data technologies;
• Expertise in designing and optimizing ETL/ELT workflows using tools such as dbt, Airflow, Azure Data Factory or Apache NiFi;
• Hands-on experience with cloud-native data platforms including Azure Synapse, Databricks, Snowflake or BigQuery;
• Knowledge of data modeling techniques including Data Vault 2.0, star schema and normalization strategies;
• Experience with large-scale distributed computing frameworks such as Apache Spark, Hadoop, Kafka or Event Hub;
• Advanced proficiency in SQL and programming languages such as Python, Scala or Java;
• Understanding of Infrastructure as Code for managing cloud-based data infrastructure;
• Skills in data security and governance best practices;
• Experience working in a federated engineering environment;
• Proficiency in observability and monitoring tools for data pipelines;
• Familiarity with Agile and DevSecOps methodologies;
• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems or a related field;
• Upper-Intermediate English language proficiency (B2+).

• No conditions specified