Data Engineer

We are currently looking for a Middle+ / Senior Data Engineer to join our Analytics Department and contribute to the development of the company’s analytical platform.

The main focus of the role is developing and optimizing our ClickHouse-based Data Warehouse, designing reliable ETL/ELT processes, and improving the overall data architecture.

Your main goal: build and maintain a scalable, reliable, and high-performance data infrastructure that supports the company’s analytics and business needs.

What experience is important to us:
At least 3 years of experience in Data Engineering, Analytics Engineering, DWH development, or a similar role.
Expert-level ClickHouse: DWH schema design, engines, partitioning, indexing, Materialized Views, optimization of complex JOINs and aggregations, system log analysis.
Advanced SQL skills.
Strong Python skills for pipeline development and automation.
Hands-on experience with Apache Airflow, including DAG development, maintenance, and monitoring.
Experience with REST APIs, Webhooks, and S3-compatible storage (MinIO / AWS S3).
Confident knowledge of Linux, Git/GitHub, and Docker.
Experience with Prometheus & Grafana.
English at B1–B2 level.
Strong systems thinking, independence, and ownership.

Will be a plus:
Experience in iGaming, FinTech, or E-commerce.
Experience designing and building a DWH from scratch.
Experience with high-load ClickHouse environments.
Basic understanding of Apache Kafka.

What you will do:
Develop and maintain the company’s ClickHouse-based DWH, including architecture, data layers, and data marts.
Design and optimize storage schemas and high-load analytical processes.
Develop and maintain ETL/ELT pipelines in Apache Airflow and ensure their reliability.
Optimize resource-intensive processes and analytical queries.
Build and maintain integrations with internal and external data sources.
Work closely with business, analytics, and engineering teams to formalize requirements and implement solutions.
Handle ad hoc data requests and research datasets.
Improve data engineering standards, maintain technical documentation, and reduce technical debt.

The position is full-time and fully remote. Due to security requirements, daily work is performed within a protected environment via remote desktop (WDS/RDS).

Interested?
If you have strong expertise in ClickHouse, SQL, Python, and Airflow, enjoy solving complex data infrastructure challenges, and want to influence how a growing analytical platform is built and scaled — we’d love to talk.

Apply for the role or reach out directly to learn more about the team, infrastructure, and challenges.