Snowflake Data Engineer

Project description

As a Snowflake Engineer, you will drive the design green field implementation of enterprise-scale data solutions on Snowflake. You will lead cross-functional teams, engage with stakeholders, and ensure delivery aligned with regulatory and architectural standards.

Responsibilities

• - Design and implementation of new/green field Snowflake data platform and architecture - Drive platform setup, integration, performance optimization and capacity planning in Snowflake - Experience with automation, CI/CD and Infrastructure‑as‑Code for Snowflake platform - Define ELT/ETL frameworks using Snowflake SQL, dbt, and enterprise ETL tools - Establish data ingestion and transformation patterns/frameworks for large-scale banking datasets - Integrate Snowflake with AWS/Azure data ecosystems and enterprise tools - Ensure compliance with APRA regulations and data governance standards - Implement security frameworks including RBAC, data masking, and encryption - Provide technical leadership, code reviews, and mentoring to engineering teams - Engage with client stakeholders for requirement analysis, solution design, and governance - Exposure to AI as it evolves within the role and the workplace

SKILLS

Must have

• - 5+ years in data engineering, with at least 4+ years in Snowflake (new greenfield platform setup implementation preferred) - Experience with dbt, Informatica, Matillion, or similar tools - Strong SQL expertise and data modelling (Kimball / Data Vault) - Hands-on experience with cloud data services (Snowflake cloud, AWS, Azure, or GCP) - Experience leading large-scale data engineering teams

Nice to have

- Banking/Financial Services experience (highly preferred) - Knowledge of payments, lending, and risk/regulatory reporting systems - Experience with Python, PySpark, and data automation frameworks - Exposure to real-time data processing (Kafka, streaming) - Familiarity with data governance tools like Collibra or Alation