Senior Data Engineer (Krakow)
First seen by Alion on Oct 9, 2026.
🌊 Data Engineer: Build the Lakehouse Behind Millions of Players
Adaptiq × a major online gaming operator
The challenge:
Our client, a major online gaming operator, is building a next-generation account management platform as a greenfield project. It runs in a highly regulated, high-volume environment where availability, sub-second performance, data integrity, and full auditability are non-negotiable, including during extreme traffic spikes.
Every transaction becomes data, and that data has to be right. How do you ingest it without losing or duplicating a single event? How do you keep it fresh and reconciled with source systems? How do you store years of history so it’s cheap to keep, fast to query, and GDPR-compliant? These are the questions you’ll answer.
Your role:
We’re looking for a hands-on Data Engineer to build scalable, reliable data infrastructure and production-grade pipelines, with a strong focus on data quality, integrity, and performance.
You’ll own the design, implementation, and operation of the data lake and lakehouse architecture, including key technical decisions. You’ll define how data is stored, partitioned, processed, and monitored, work closely with Data Engineering, DevOps, Data Science, and other stakeholders, and help shape the platform’s long-term scalability and the data migration.
What you’ll do:
Build and maintain a multi-layer lakehouse (bronze / silver / gold) on Iceberg or Delta, including schema evolution
Design CDC and streaming ingestion with Kafka, Debezium, or similar, handling late and duplicate events
Optimize data layout in cloud object storage: partitioning, compaction, file sizing, query performance
Define retention, archival, immutability, and GDPR-style deletion processes
Ensure data freshness, quality, and consistency; detect drift and reconcile with source systems
Implement governance: metadata, lineage, access controls, PII protection, encryption, audit trails
Monitor pipelines and drive resolution of data anomalies
Collaborate with Analytics, Finance, and Compliance on requirements, migration, and architecture
What you bring:
5+ years in data engineering with large-scale data lakes or lakehouse environments
Production experience with cloud object storage (AWS S3 or equivalent) and an analytics platform such as Snowflake, Databricks, or BigQuery
Hands-on expertise with Iceberg, Delta, or Hudi, plus solid knowledge of partitioning, file layout, and query optimization
Experience building CDC and streaming pipelines (Kafka, Debezium, or similar)
Strong SQL, data modeling, and understanding of relational and transactional data
Experience with data quality, monitoring, and governance: lineage, access control, PII handling, retention
Python and workflow orchestration (Airflow or Dagster)
Ability to own technical decisions and clearly explain trade-offs
Bonus points:
✦ Financial, transactional, or ledger data
✦ Regulated or audit-heavy environments: fintech, gaming, banking, payments
✦ Large-scale data migration projects
If you want your pipelines to carry real money, real scale, and real responsibility, let’s talk.