Snowflake Data Engineering Consultant

About the role

We are seeking an experienced Analytics/Data Engineer with strong expertise in Snowflake, SQL, dbt, Python, and dimensional data modeling. The role focuses on transforming complex banking and financial data into scalable enterprise analytics solutions while ensuring performance, security, and data quality.

Key responsibilities

• Architect and build dimensional data models (Kimball star or snowflake schema) around Jack Henry core banking structures.
• Design dbt transformation pipelines that integrate external third‑party data feeds with the core banking foundation.
• Develop, test, and document modular dbt models, including automated data‑quality checks and GitHub version control.
• Collaborate with Python developers to process, flatten, and model raw JSON/API payloads from Jack Henry and other vendors.
• Optimize Snowflake virtual warehouses, role‑based access controls, clustering, and query execution for banking analytics.

Required profile

• 3+ years of direct experience with Jack Henry or similar core banking data structures.
• Deep expertise in Snowflake architecture, complex SQL, and handling semi‑structured JSON/VARIANT data.
• Proven track record building production‑grade dbt models, tests, and documentation.
• Strong background in Kimball methodology, slowly changing dimensions (SCDs), and financial data modeling.
• Hands‑on experience with Python API ingestion, GitHub, Postman, and hybrid Linux/Azure environments.

Required skills

• Snowflake
• SQL
• dbt
• Python
• Dimensional data modeling
• Kimball methodology
• Slowly changing dimensions (SCD)
• JSON/VARIANT handling
• GitHub
• Postman
• Azure
• Linux