Hello! We are developing Riorise — a mobile MMO RPG. The game combines open-world, roleplay RP, life simulator, racing, and a social sandbox where thousands of players interact in real-time.
We are looking for a Data Engineer who will be responsible for the reliability, performance, and development of our analytical platform. We have a lot of event data, ClickHouse, Airflow, dbt, BI reports, and product data marts.
What you will be doing:
- Designing, maintaining, and optimizing ETL/ELT processes in Airflow: regular incremental loads, backfill, cleanup, full-refresh, historical data processing.
- Developing ClickHouse storage: designing tables, partitioning, sorting keys, TTL/cleanup logic, optimizing heavy queries, and reducing unnecessary full scans on large tables.
- Working with event streams: ingestion from RabbitMQ/raw event tables, deduplication, JSON event parsing, gap control, recovery of unprocessed events.
- Supporting and developing dbt models and BI data marts: product reports, aggregates, historical snapshots, data completeness and correctness control.
- Investigating data incidents: why a report is half-empty, where historical values disappeared, why a DAG started running longer, why a queue is accumulating, what data can be recovered from the raw layer.
- Building data quality and freshness monitoring: pipeline lags, incoming/processed event volumes, gaps by date/category, anomalies in data marts, DAG/task duration.
- Optimizing existing processes, not just adding new ones: removing inefficient anti-join/NOT IN, heavy FINAL, full OPTIMIZE, unnecessary 90-day cleanup cycles, unjustified full-refresh.
- Making data recovery manageable: safe backfill scenarios, batching, result verification, repeatable procedures for restoring data marts and raw/event streams.
- Documenting critical pipelines: sources, SLA, deduplication logic, how to perform backfill, where to check the backlog, which tables are the source of truth.
- Collaborating with analysts and product managers: quickly understanding which data mart affects a report, what events the business needs, and how a technical problem manifests in product analytics.
What we are looking for:
- Solid SQL skills and experience optimizing queries on large data volumes.
- Practical experience with ClickHouse or similar columnar OLAP storage.
- Experience with Airflow: DAGs, retries, timeouts, backfill, dependency management, diagnosing long-running tasks.
- Understanding of event-driven data pipelines: queues, raw events, idempotency, deduplication, late events.
- Experience with dbt or a similar approach to analytical modeling.
- Readiness to combine data engineering, AI tools, and practical automation of internal processes.
- Ability to investigate problems systematically: from a symptom in a BI report to a specific query, table, sorting key, or broken cleanup logic.
- Desire to work not only on "delivering data" but also on the reliability of the entire data platform.
What we offer:
- Fully remote work;
- Flexible schedule — we focus on results, not hours;
- Voluntary medical insurance after the probationary period;
- Opportunity to directly influence the growth of an international gaming project;
- Great freedom in testing hypotheses, formats, and approaches;
- A team focused on rapid iterations and scaling successful solutions.
