Data Engineer - Modern Stack
Building warehouses and lakehouses on Snowflake and Microsoft Fabric. A modern data stack for the AI layer.
- Team
- Custom Development & Data
- Level
- Mid / Senior
- Location
- Warsaw or remote from Poland
- Engagement
- B2B or employment contract
SnowflakeMicrosoft FabricdbtPythonSnowpark
Responsibilities
- Designing and building data warehouses and lakehouses on Snowflake and Microsoft Fabric
- Data modelling (dbt, Kimball, Data Vault 2.0), lineage and documentation
- Data integrations with SAP (OData, BAPI, CPI), M365, SaaS and on-premise systems
- Preparing data for the AI and RAG layer (classification, chunking, embedding)
- Implementing data governance policies: Microsoft Purview, Snowflake Horizon
- Building and maintaining ELT pipelines (Azure Data Factory, dbt, Snowpipe)
- Working with clients on data quality audits and SNOK MDM planning
Requirements
- At least 3 years of experience in data engineering or analytics engineering
- Practical knowledge of Snowflake or Microsoft Fabric in a production environment
- Proficiency in SQL and Python (pandas, PySpark a plus)
- Experience with dbt (Core or Cloud) and data modelling
- Knowledge of data integration patterns: batch, streaming, CDC
- Ability to work with Git, basic CI/CD for pipelines
Nice to have
- Familiarity with SAP and its data model (EKKO, BKPF, PA/HR tables)
- Experience with Databricks (Delta Lake, Unity Catalog, MLflow)
- Knowledge of BigQuery and the Google Cloud ecosystem
- Snowflake certifications (SnowPro Core / Advanced) or Microsoft Fabric
- Experience with Master Data Management or data quality
What we offer
- Work on SNOK MDM - SNOK's own product, live in production at enterprise clients
- B2B pay 16,000 - 26,000 PLN net, or an equivalent employment contract
- Access to Snowflake, Microsoft Fabric and Databricks environments from day one
- Budget for certifications and conference attendance (Snowflake Summit, dbt Coalesce)
- Projects in regulated sectors - banking, insurance, manufacturing, healthcare
- Opportunity to grow into the AI/ML stack - LLMs on client data