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Mid-level, metro location, and recognizable employer create moderate applicant density.
Core analytics engineering skills transfer across industries, but strong supply-chain domain experience is preferred.
Explicit 5+ years plus specific Snowflake, dbt, and supply-chain analytics requirements increase selectivity.
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Design, build, and maintain scalable data pipelines and curated datasets using Python, dbt, Airflow, and Snowflake to support supply chain and operations analytics.
Develop user-centric interactive web applications for data exploration, reporting, and workflow automation leveraging Python frameworks like Plotly Dash, Panel, and FastAPI.
Lead technical design decisions, ensure alignment with data governance and compliance, and mentor junior engineers within supply chain, logistics, and manufacturing domains.
5+ years experience in analytics engineering, data engineering, or full-stack development.
Strong Python programming skills with experience in Dash, Panel, or similar open-source frameworks and REST API development using FastAPI or Flask.
Proficiency in SQL, advanced data modeling, and experience with cloud data warehouses—Snowflake strongly preferred.
Bachelor's or Master’s degree in Computer Science, IT, Engineering, or related field.
Experienced in supply chain, logistics, manufacturing, or operations analytics environments with ability to translate business needs into technical solutions.
Skilled at building scalable, maintainable full-stack Python data applications integrated with modern data platforms and APIs.
Operates well in collaborative, cross-functional teams with stakeholders across supply chain and analytics functions and leads best practices and mentoring initiatives.