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Principal Data Engineer – Snowflake - Sydney - AI Talent
Description
We are seeking a Principal Data Engineer to lead our data strategy and platform migration within a leading FinTech organisation.
This role is critical for architecting and executing the large-scale shift from our current AWS/Redshift environment to the modern Snowflake Data Cloud.
This position demands over a decade of data expertise, mastery of distributed processing, and a proven ability to deliver high-performance, secure, and resilient data solutions.
Key ResponsibilitiesLead Data Architecture:
Define the end-to-end data architecture, standards, and governance practises for the target Snowflake platform, ensuring scalability, compliance, and cost optimisation.
Cloud Migration Strategy:
Design and execute the complex migration of data, ETL/ELT pipelines, and BI workloads from AWS Redshift to Snowflake.
High-Performance Development:
Develop, optimise, and manage complex data pipelines using Python/PySpark to handle massive data volumes in a distributed computing environment.
Snowflake Expertise:
Master the implementation of native Snowflake features, including continuous data loading using Snowpipe, managing data access and query utilities using SnowSQL, and leveraging zero-copy cloning.
Platform Governance:
Define and implement robust security protocols, role-based access controls, and data encryption standards compliant with financial sector regulations.
Mentorship:
Provide technical leadership and guidance to data engineering teams on best practises for cloud data warehousing and distributed programmes.
Required Technical ExpertiseThe ideal candidate must demonstrate exceptional depth across all specified platforms:
Total Experience:
Over 10 years of overall professional experience in data engineering or architecture.
Snowflake:
Over 5 years of hands-on experience, including Snowpipe and SnowSQL development.
Cloud Data Warehousing:
Over 5 years of experience specifically with AWS Redshift.
Distributed Processing:
Over 5 years of experience in Python/PySpark for large-scale ETL/ELT development.
Platform Exposure:
Significant exposure and integration experience across AWS, Redshift, and Snowflake within the last 5 years.
Languages:
Expert-level proficiency in SQL and Python.
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