Snowflake Developer

Job Description We are seeking an experienced Analytics Engineer / Data Engineer on a contract basis to lead the ingestion, modeling, and transformation of our core banking data into Snowflake. Our software team operates in a hybrid environment (on-premise Linux and Azure) using Python, GitHub, and Postman to integrate third-party vendor APIs. In this role, your primary objective will be modeling raw Jack Henry core banking data landed in Snowflake, transforming it into production-grade dimensional models using dbt and SQL, and appending key ancillary data sources (loans, deposits, digital banking, and compliance feeds) to create a unified enterprise analytics layer.

Key Scope of Work & Deliverables “ Jack Henry Core Data Modeling: Architect and build dimensional data models (Kimball star schema/snowflake schema) around Jack Henry core banking structures (accounts, transactions, customer profiles, general ledger). “ Ancillary Data Integration: Design dbt transformation pipelines that join and append external third-party data feeds to the Jack Henry core data foundation. “ dbt Pipeline & Testing: Develop, test, and document modular dbt transformation models, incorporating automated data quality checks and version control via GitHub. “ API Payload Transformation: Collaborate with our Python developers to process, flatten, and model raw JSON/relational API payloads landed from Jack Henry and other vendor interfaces. “ Snowflake Performance & Security: Optimize virtual warehouses, role-based access controls (RBAC), clustering, and query execution for banking analytics.

” Core Banking Domain: Direct experience working with Jack Henry core banking system data structures or similar core financial platforms. “ Snowflake & SQL: Deep expertise in Snowflake architecture, complex SQL, and handling semi-structured data (parsing JSON/VARIANT payloads). “ dbt Expertise: Proven track record building production dbt models, data quality tests, and documentation. “ Dimensional Modeling: Strong background in Kimball methodology, slowly changing dimensions (SCDs), and financial data modeling. “ Technical Stack Familiarity: Hands-on experience working alongside Python API ingestion workflows, GitHub version control, Postman API testing, and hybrid Linux/Azure environments