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myGwork - LGBTQ+ Business Community Logo myGwork - LGBTQ+ Business Community · IT - Software Development

Database Engineer

Poland · Job Posted March 04, 2026
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Job Description

We're hiring a Database Engineer to design, build, and operate reliable data platforms and pipelines. You'll focus on robust ETL/ELT workflows, scalable big data processing, and cloud-first architectures (Azure preferred) that power analytics and applications.

Job Responsibility

  • Design, build, and maintain ETL/ELT pipelines and data workflows (e.g., Azure Data Factory, Databricks, Spark, ClickHouse, Airflow, etc.)
  • Develop and optimize data models, data warehouse/lake/lakehouse schema (partitioning, indexing, clustering, cost/performance tuning, etc.)
  • Build scalable batch and streaming processing jobs (Spark/Databricks, Delta Lake
  • Kafka/Event Hubs a plus)
  • Ensure data quality, reliability, and observability (tests, monitoring, alerting, SLAs)
  • Implement CI/CD and version control for data assets and pipelines
  • Secure data and environments (IAM/Entra ID, Key Vault, strong tenancy guarantees, encryption, least privilege)
  • Collaborate with application, analytics, and platform teams to deliver trustworthy, consumable datasets

Requirements

  • ETL or ELT experience required (ADF/Databricks/dbt/Airflow or similar)
  • Big data experience required
  • Cloud experience required
  • Azure preferred (Synapse, Data Factory, Databricks, Azure Storage, Event Hubs, etc.)
  • Strong SQL and performance tuning expertise
  • hands-on with at least one warehouse/lakehouse (Synapse/Snowflake/BigQuery/Redshift or similar)
  • Solid data modeling fundamentals (star/snowflake schemas, normalization/denormalization, CDC, etc.)
  • Experience with CI/CD, Git, and infrastructure automation basics
  • Work as an Independent Contractor

Nice to have

  • Streaming pipelines (Kafka, Event Hubs, Kinesis, Pub/Sub) and exactly-once/at-least-once patterns
  • Orchestration and workflow tools (Airflow, Prefect, Azure Data Factory)
  • Python for data engineering
  • Data governance, lineage, and security best practices
  • Infrastructure as Code (Terraform) for data platform provisioning
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