Senior Data Engineer (Scala, Spark, Airflow)
Hypercell Games is a mobile game studio behind some of the most downloaded hybrid-casual and puzzle titles on the market.
Our games reach millions of players worldwide.
What you can definitely know about us:
- Sand Balls game –360 M+
- Rope and Balls – 62 M+
- Freaky Stan – 52 M+
- Garden Balls – 22 M+
- Unpuzzle – 22 M+
- Run&Gun – 13 M+
We're looking for a Senior Data Engineer to own and evolve the data platform supporting our publishing portfolio. You'll be responsible for building and maintaining ETL/ELT pipelines (Spark/Scala + Airflow), developing and optimizing BigQuery data layers, and ensuring reliable, high-quality data across multiple products and data sources. This is a highly autonomous individual-contributor role embedded within the Analytics team, with close day-to-day collaboration with analysts and full ownership of your technical domain.
- Genres: Puzzle, Casual, Hyper-casual, Shooter
- Platforms: Mobile, iOS, Android
- Design, develop, and maintain ETL/ELT pipelines (Spark, Scala, Airflow).
- Orchestrate workflows in self-managed Apache Airflow.
- Develop and optimize data layers in BigQuery, including external tables on GCS and cost-aware data structures.
- Process large volumes of data using Spark/Scala.
- Ensure data quality through validation, monitoring, alerting, and cross-source data reconciliation.
- Prepare and maintain data marts for analytics needs.
- Document infrastructure and data pipelines.
- Contribute to the development of the analytics platform.
- Monitor and optimize storage and query costs.
- 4+ years of experience as a Data Engineer, including production experience with Spark.
- Strong Scala skills (primary ETL language), with production Spark experience specifically on Scala.
- Advanced SQL, including window functions and query optimization.
- Experience with self-managed Apache Airflow, including writing and maintaining DAGs.
- Hands-on experience with BigQuery; experience with external tables, GCS storage, and cost optimization is a strong plus.
- Python for auxiliary tasks and analytics.
- Strong understanding of ETL/ELT concepts and pipeline design.
- Experience with data warehousing and data modeling (layers, fact/dimension).
- Experience with Git, CI/CD, and end-to-end pipeline testing.
- Experience with data quality practices, including validation, monitoring, and alerting.
- Comfortable working with AI-assisted development tools; our team actively uses Claude Code.
- Experience working closely with analysts and supporting analytical data needs.
- Ability to work independently, take ownership of the area of responsibility, and proactively drive solutions.
- Ability to explain technical decisions to non-technical colleagues.
- English and Russian languages.
Nice to have:
- Experience optimizing BigQuery costs (partitioning, clustering, external tables, materialized views, query tuning).
- Experience with advertising and attribution data, including MMPs such as Adjust and AppsFlyer.
- Understanding of layered data architecture (raw → staging → marts, medallion architecture, etc.).
- Kubernetes (ideally GKE).
- Infrastructure as Code (Terraform or similar).
- Experience with BI tools such as Superset, Tableau, or Power BI, and preparing data for visualization.
- The opportunity to work on games played by millions of players.
- Implement your bold ideas.
- Paid vacation.
- Support for professional development (training, coaching, and more).
- Opportunity to grow and develop with the company.
- Supportive and warm working atmosphere within the team.
The selection process
- HR interview
- Final interview which includes the technical part
