Role OverviewThe Data Engineer serves as the hands-on architect of the enterprise data supply chain for the organization's most advanced analytics, data science, and AI initiatives. This role performs critical engineering work required to deliver high-fidelity, production-grade data that powers machine learning models, feature stores, and generative AI applications.
What You Will Do
Designs, builds, and maintains resilient ETL/ELT pipelines, develops and maintains feature stores and analytically optimized datasets, engineers data pipelines for generative AI use cases, and acts as a Snowflake power user and technical lead.
Why It Might Be a Fit
The ideal candidate will have a strong understanding of the specific data needs for Machine Learning and Generative AI, a 'get-it-done' attitude, and the ability to navigate enterprise bureaucracy and technical debt to ship code at the required speed.
Requirements
- Master's degree in Computer Science, Data Engineering, or a related field from an accredited college or university
- Six (6) years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environments
- Expert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and the integration of Snowflake with external cloud AI services
- Advanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services
- Mastery of Python, SQL, and PySpark
- Proven ability to interface with 'old world' tech (on-premise SQL, Mainframe extracts, flat files) and transform it for modern cloud consumption
- A strong understanding of the specific data needs for Machine Learning (feature engineering) and Generative AI (vectorization and embedding pipelines)
- A 'get-it-done' attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office
- Ability to work in a team environment
- Ability to meet or exceed Performance Competencies
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