Data Engineer

📋 Description

• Build and operate a realtime data platform for analytics.
• Design data models and transformation pipelines (dbt, SQL, Python).
• Ingest data from ETLs, CDC, APIs, CSVs, and event streams.
• Ensure data quality and reliability for decision-making.
• Collaborate with analysts and stakeholders to deliver insights.
• Expose data via APIs and semantic layers for self-service.

🎯 Requirements

• 3+ years in BI engineering, data engineering, or analytics.
• SQL skills and experience with a data warehouse (Athena/Redshift/BigQuery).
• Dimensional modeling, dbt, star/snowflake schemas.
• Python for data transformations.
• Data quality: validation, deduplication, audit logs.
• CI/CD and infra: GitHub Actions, Terraform/CDK basics.

🎁 Benefits

• Shape BI architecture from the ground up.
• Modern realtime analytics stack (dbt, Cube, Grafana, Postgres, Iceberg).
• Collaborative engineering-led environment with analytics focus.
• Work remotely or in a hybrid style.
• Prague offices with language courses.
• Quarterly team-building activities.