Data Engineer

Grid Dynamics is a technology consulting, platform and product engineering, AI, and advanced analytics services provider that solves technical challenges and enables business outcomes for enterprise companies undergoing transformation.

• Partner with engineers across the team to operate and evolve the data platform;
• Work closely with Data Scientists, providing technical support and ensuring smooth day-to-day operations;
• Build, maintain, and improve CI/CD pipelines for data workflows;
• Manage and optimize Spark infrastructure supporting a high volume of jobs;
• Manage Kubernetes resources for on-prem workloads;
• Implement and maintain authentication and data governance practices;
• Handle file compaction and maintenance across HDFS and object stores;
• Design and maintain partitioning strategies, schemas, and type-safe data models using table formats like Iceberg/Hive;
• Set up and maintain observability tooling and participate in on-call rotations;
• Collaborate cross-functionally as a strong team player across engineering and data science teams.

• Strong hands-on expertise with CI/CD pipelines;
• Solid experience with Spark infrastructure at scale;
• Background in distributed systems;
• Experience managing Kubernetes resources;
• Practical knowledge of authentication and data governance principles;
• Familiarity with file compaction and maintenance on HDFS or object stores;
• Strong grasp of data engineering fundamentals: partitioning, schema design, type safety, and table formats;
• Experience with observability and on-call practices, including alerting setup;
• Proficiency in Python and Airflow;
• Experience with Kubernetes (on-prem) and Docker;
• Familiarity with Trino/Presto;
• Strong communicator and collaborator, comfortable working cross-functionally;
• Nice to have: Scala.

• Competitive salary;
• Flexible schedule;
• Medical insurance;
• Sports benefits;
• Corporate social events;
• Professional development opportunities;
• Well-equipped office.