Data Engineer (Snowflake)

Quick Facts

• Role: Data Engineer (Snowflake)

Description

You will lead Snowflake architecture for a long-term, multi-year data platform program at a major bank. The platform sources, normalizes, and models data from many raw systems to deliver trusted datasets for business decisions, risk analysis, and regulatory reporting. You will guide a strategic migration from Snowpark (Scala) to dbt + Python while keeping the production environment performant, secure, and cost-effective.

Responsibilities

• Be the team’s go-to authority on Snowflake architecture (warehouse strategy, multi-cluster scaling, clustering keys, micro-partition pruning, query profiling, and performance diagnostics)
• Define Snowflake project structure and migration standards (database/schema/warehouse layout, environment separation, naming conventions, and scalable patterns for ~300 transformation jobs)
• Own security and access architecture (RBAC role hierarchy, secure views, data masking policies, and data-sharing design)
• Review migration designs from a Snowflake-native perspective (materialization strategy, incremental load patterns, and warehouse usage per workload)
• Assess existing Snowpark/Scala transformation code to determine what migrates cleanly vs. what will perform poorly once rebuilt
• Drive cost governance and compute efficiency (resource monitors, warehouse right-sizing, identifying poorly-tuned workloads)
• Mentor engineers on Snowflake internals and performance reasoning

Requirements

• Expert-level Snowflake architect with hands-on experience in large, regulated data environments
• Proven experience architecting data platforms at scale (how environments, schemas, and workloads are organized for scalability and maintainability)
• Strong software engineering fundamentals in Scala or Python; 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 for architecture discussions; able to push back on designs, explain trade-offs clearly, and make decisions when needed
• Preferred: experience in financial services or banking domains

Must Have

• Snowflake: micro-partitions, clustering, query optimization, virtual warehouse sizing, multi-cluster scaling, caching
• Snowflake security architecture: RBAC, secure views, masking policies, data sharing
• Advanced SQL
• 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