Data Engineer (Snowflake)

We are looking for a Data Engineer (Snowflake) for one of our clients within Banking & Finance.

Start date: 2026-11-02
End date: 2027-01-31
Location: Stockholm

About the assignment:
You will serve as the lead Snowflake architecture authority for a long-term, multi-year data platform program at a major bank. The platform sources, normalizes, and models data from numerous raw systems to deliver trusted datasets for critical business decisions, risk analysis, and regulatory reporting. You will guide the team through a strategic migration from Snowpark (Scala) to DBT + Python while ensuring the production platform remains performant, secure, and cost-effective.

Core Responsibilities:

• Act as the team's go-to authority on Snowflake architecture: warehouse strategy, multi-cluster scaling, clustering keys, micro-partition pruning, query profiling, and complex performance diagnostics
• Define Snowflake project structure and standards for the migration: database/schema/warehouse layout, environment separation, naming conventions, and patterns that scale across ~300 transformation jobs
• Own security and access architecture including RBAC role hierarchy, secure views, data masking policies, and data-sharing design
• Partner with the migration team to review designs from a Snowflake-native perspective: materialization strategy, incremental load patterns, and warehouse usage per workload
• Read and assess existing Snowpark/Scala transformation code to identify what migrates cleanly versus what will perform poorly once rebuilt
• Drive cost governance and compute efficiency: resource monitors, warehouse right-sizing, and identifying poorly-tuned workloads
• Mentor engineers on Snowflake internals and performance reasoning

Profile & Qualifications:

• Expert-level Snowflake architect with hands-on experience in large, regulated data environments
• Proven experience architecting data platforms at scale — not just pipelines, but deciding how environments, schemas, and workloads should be organized for scalability and maintainability
• Strong software engineering fundamentals in Scala or Python, comfortable with object-oriented concepts and able to read, review, and reason about Snowpark (Scala) code
• Deep SQL and data modeling expertise at scale, including dimensional modeling and partitioning/incremental load strategies
• Confident technical anchor in architecture discussions — able to push back on designs, explain trade-offs clearly, and make decisions when needed
• Experience working in financial services or banking domains preferred

Must Have:

• Snowflake (expert level: micro-partitions, clustering, query optimization, virtual warehouse sizing, multi-cluster scaling, caching)
• Snowflake security architecture (RBAC, secure views, masking policies, data sharing)
• SQL (advanced)
• Scala or Python (solid fundamentals)
• Data modeling at scale

Nice to have:

• Snowpark (Scala or Python)
• dbt
• Snowflake certification (SnowPro Advanced: Architect or Data Engineer)
• CI/CD tooling and data-quality/testing frameworks
• Airflow
• GitHub Copilot or similar AI coding assistants