{"id":3466516,"url":"https://alion.io/job/adaptiq-senior-data-engineer-krakow","title":"Senior Data Engineer (Krakow)","company":{"id":4485822,"name":"Adaptiq","domain":"adaptiq.co","url":"https://alion.io/company/adaptiq","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ukraine"],"countries":["UA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":6800,"max":7800,"currency":"USD","period":"month","gross":false,"usd_annual":93600},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"GDPR","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-09T11:53:20Z","employer_posted_date":null,"last_verified_at":"2026-10-09T11:53:20Z","board_verified":false,"closed_at":null,"days_open":23,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":23},"description":"🌊 Data Engineer: Build the Lakehouse Behind Millions of Players\n\nAdaptiq × a major online gaming operator\n\nThe challenge:\n\nOur 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.\n\nEvery 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.\n\nYour role:\n\nWe’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.\n\nYou’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.\n\nWhat you’ll do:\n\nBuild and maintain a multi-layer lakehouse (bronze / silver / gold) on Iceberg or Delta, including schema evolution\n\nDesign CDC and streaming ingestion with Kafka, Debezium, or similar, handling late and duplicate events\n\nOptimize data layout in cloud object storage: partitioning, compaction, file sizing, query performance\n\nDefine retention, archival, immutability, and GDPR-style deletion processes\n\nEnsure data freshness, quality, and consistency; detect drift and reconcile with source systems\n\nImplement governance: metadata, lineage, access controls, PII protection, encryption, audit trails\n\nMonitor pipelines and drive resolution of data anomalies\n\nCollaborate with Analytics, Finance, and Compliance on requirements, migration, and architecture\nWhat you bring:\n\n5+ years in data engineering with large-scale data lakes or lakehouse environments\n\nProduction experience with cloud object storage (AWS S3 or equivalent) and an analytics platform such as Snowflake, Databricks, or BigQuery\n\nHands-on expertise with Iceberg, Delta, or Hudi, plus solid knowledge of partitioning, file layout, and query optimization\n\nExperience building CDC and streaming pipelines (Kafka, Debezium, or similar)\n\nStrong SQL, data modeling, and understanding of relational and transactional data\n\nExperience with data quality, monitoring, and governance: lineage, access control, PII handling, retention\n\nPython and workflow orchestration (Airflow or Dagster)\n\nAbility to own technical decisions and clearly explain trade-offs\nBonus points:\n\n✦ Financial, transactional, or ledger data\n\n✦ Regulated or audit-heavy environments: fintech, gaming, banking, payments\n\n✦ Large-scale data migration projects\n\nIf you want 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