Data engineer in iGaming

GR8_TECH builds B2B iGaming platforms for operators who play to lead. We deliver full-cycle, high-impact tech designed to scale — from seamless integrations and expert consulting to long-term operational support. Our platform powers millions of active players and drives real business growth. Call it what it is: the iGaming Platform for Champions. With 1000+ GR8 people across locations and time zones, we don’t just ship technology — we help operators build success stories across brands, markets, and geos. Our ambition drives us. Our people make it real. If you’re a challenger in spirit and a champion in action — join us.

• Design and implement scalable data transformation layers, organizing raw data into validated, production-grade data marts.
• Build and optimize semantic layer models, ensuring consistent metrics and definitions across all reporting surfaces.
• Establish data modeling standards utilizing optimal storage formats (Parquet, ORC, AVRO) and storage engines (PostgreSQL, ClickHouse, Redshift/BigQuery).
• Ship and maintain end-to-end data ingestion pipelines integrating internal services and third-party event streams (Kafka, Kinesis, external APIs).
• Automate data quality and integrity testing to catch pipeline breaks and silent schema drifts before they reach downstream consumers.
• Tune query performance and pipeline bottlenecks, actively managing indexing, data partitioning, and job scheduling.
• Expose data-centric services by building and managing performant REST APIs using modern frameworks (FastAPI, Flask, or Aiohttp).
• Enforce granular access control across our data layers via RBAC, row-level security (RLS), and column-level masking.
• Automate CI/CD workflows and deployments using Docker, GitLab CI, and Terraform across our cloud infrastructure.
• Partner with product managers, software engineers, and analysts to translate business logic into maintainable technical requirements.
• Participate in thorough code and architecture reviews, upholding strict testing standards (unit, integration, TDD/BDD).
• Document system designs and data catalog schemas, making data discoverable and self-serve across the organization.

• 3+ years of production experience in Data Engineering, Software Engineering, or related distributed data systems.
• Proven SQL & Database expertise: Strong hands-on work with relational databases (PostgreSQL) and modern analytical/columnar data warehouses (ClickHouse, BigQuery, or Redshift).
• Demonstrated pipeline & distributed compute skills: Practical experience orchestrating distributed jobs (Spark, Trino, Flink) and handling event streaming engines (Kafka, RabbitMQ, or Kinesis).
• Solid software engineering foundations: Proficient in writing clean, modular Python for data applications, pipeline orchestration, and REST APIs.
• Linux, Container, & CI/CD literacy: Comfortable writing Dockerfiles, configuring CI/CD pipelines (GitLab CI, GitHub Actions), and utilizing Git version control.
• Data quality discipline: Direct experience implementing automated data testing, schema validation, and pipeline observability.
• Будет плюсом: Hands-on experience with Infrastructure as Code (Terraform) and AWS cloud services; Practical exposure to metadata management tools (DataHub, OpenMetadata); Understanding of resilience patterns in distributed systems (circuit breakers, rate limiting, connection pooling); Degree in Computer Science, Software Engineering, or equivalent practical experience

• annual budget you allocate to: Sports, Medical, Mental health, Home office, Languages.
• Paid maternity/paternity leave + monthly childcare allowance.
• 20+ vacation days, unlimited sick leave, emergency time off.
• Remote-first + tech support + coworking compensation.
• Team events (online/offline/offsite).
• Learning culture with internal courses + growth programs.