[Hiring] Lead Data Developer @EPAM Systems

Role Description

We are on the lookout for an accomplished Lead Data Engineer to join our team and help architect, expand, and fortify the data platform behind our industry-leading Unified Communications and Collaboration (UCC) reporting stack.

• Troubleshoot and improve data modeling approaches spanning OLTP (Postgres) and OLAP (StarRocks) database environments.
• Plan and carry out schema updates, backfills, and large-scale migrations while keeping services running smoothly.
• Fine-tune query performance and refine storage architecture to serve both transactional and analytical needs.
• Suggest continuous enhancements and shape architectural choices that support scaling the analytics platform.

Qualifications

• At least 5 years of relevant hands-on professional experience.
• A minimum of one year of experience in a leadership or team management role.
• Substantial, practical experience functioning as a DBA or data engineer working with relational databases such as PostgreSQL at scale.
• Deep familiarity with OLAP technologies, including StarRocks or comparable columnar/analytics database systems.
• Background in data warehousing principles and implementation.
• Skilled at diagnosing and optimizing query performance and storage structure across both OLTP and OLAP environments.
• Working knowledge of software development using Kotlin or Golang.
• Strong preference for designing data solutions that are performant, efficient, and reliable at scale.
• Self-driven and team-oriented, comfortable working autonomously while also guiding and mentoring colleagues.
• Solid communication skills for collaborating effectively with team members and stakeholders alike.
• Strong written and spoken proficiency in English at a B2 level or higher.

Requirements

• Experience with AWS Aurora for handling scalable relational database management.
• Knowledge of data modeling practices that support dependable and efficient data structures.
• Expertise in database performance tuning to enhance query speed and storage efficiency.
• Familiarity with Docker for building and managing containerized services.
• Working knowledge of Java for various software development tasks.
• Experience with Kubernetes for managing and scaling containerized workloads.
• Familiarity with Terraform for provisioning infrastructure through code.
• Comfortable operating within Unix-based environments, including Linux for pods and macOS for workstations.
• Background working with data engineering pipelines, including technologies such as Flink, Kafka, and ETL/ELT workflows.