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Senior Data Platform Engineer



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ING Hubs Poland is hiring!


The expected salary for:

senior specialist position: 9600 - 22 000 PLN

expert position: 13 000 - 28 000 PLN


The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.


We are looking for you, if you:

  • have 4+ years of experience in Data Engineering, Platform Engineering, Infrastructure Engineering, or Site Reliability Engineering
  • have hands-on experience in at least one of the following domains and practical knowledge of related technologies:
    • Data Processing & Analytics: Apache Spark, DBT, Python, SQL, BigQuery, Trino
    • Data Lake & Storage: Apache Iceberg, Hive Metastore, MinIO/S3-compatible Object Storage, Google Cloud Storage
    • Platform & Infrastructure: Kubernetes, Docker, Linux, Keycloak, Ceph, Ingress / Networking
    • Reliability & Operations: Monitoring, Logging, Alerting, Data Replication, Backup & Restore, Disaster Recovery
  • have experience building, operating, or supporting modern data platforms and distributed data processing environments
  • have practical experience with Google Cloud Platform (GCP) and cloud-native technologies
  • have experience with automation, CI/CD, and infrastructure-as-code practices

You'll get extra points for experience with:

  • Airflow-based orchestration platforms
  • Keycloak, Ceph, or enterprise-scale platform services
  • designing and operating large-scale data platforms
  • disaster recovery, business continuity, or fallback solutions
  • modern lakehouse architectures based on Apache Iceberg
  • data replication and synchronization at scale
  • migrating workloads between cloud and on-premise environments

Your responsibilities will relate to:

  • designing, building, and maintaining ING’s Data Analytics Fallback Platform
  • creating resilient data platform capabilities that support critical business workloads during disaster recovery and fallback scenarios
  • developing and operating solutions based on Apache Spark, Apache Airflow, Apache Iceberg, Trino, and object storage technologies
  • building and maintaining data processing, orchestration, storage, and metadata-management capabilities
  • implementing replication, synchronization, reconciliation, and recovery mechanisms for critical datasets
  • building and optimizing analytical and batch-processing pipelines using modern cloud and data technologies
  • improving platform observability through monitoring, logging, alerting, and operational readiness practices
  • ensuring platform reliability, security, recoverability, and operational resilience
  • implementing backup, restore, disaster recovery, and business continuity capabilities
  • collaborating with platform, infrastructure, security, and data engineering teams across ING
  • contributing to architecture decisions, engineering standards, automation initiatives, and technical roadmaps
  • participating in support, operational readiness, and on-call activities where required

Information about the squad:

You will join a team building the VISTA (Data Analytics) Fallback Platform, a strategic initiative focused on ensuring operational resilience and business continuity for ING’s data and analytics ecosystem.

The platform provides fallback capabilities for critical analytical and reporting workloads by leveraging modern lakehouse and data platform technologies. The solution is designed to enable rapid recovery and continued operation of key business processes during crisis scenarios.


We value ownership, innovation, collaboration, and continuous improvement. You will have the opportunity to work on one of ING’s most strategic engineering initiatives and help shape the future of resilient data platforms.


The role naming convention in the global ING job architecture will be “Engineer III” or “Engineer IV”. This position is intended to strengthen the team responsible for delivering and operating the VISTA Fallback solution, combining expertise in Data Engineering, Platform Engineering, and Reliability Engineering.

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