Senior Analytics Engineer

Role Overview

Senior Analytics Engineer (3–6 month contract with a hire opportunity). Hybrid or 100% remote. You will be a senior individual contributor owning analytics systems end-to-end and translating complex business processes into production-ready data workflows used daily across Supply Chain, Finance, and Commercial operations.

Responsibilities

• Own end-to-end ingestion of the demand plan into Databricks and Tableau
• Maintain and improve demand cascade logic from customer-level to retailer-level
• Manage unit conversions and product mappings across finished goods, cases, pallets, and materials
• Ensure demand data is accurate, timely, and consumable by downstream supply chain tools
• Design, build, and maintain data pipelines in Databricks using Python and SQL
• Ingest from multiple sources, including retailer APIs, ERP systems (NetSuite), and Azure Blob Storage file drops
• Own data table design, transformations, and performance optimization at scale (millions of records/day)
• Improve reliability, documentation, and resilience of data pipelines
• Ensure dashboards are accurate, performant, and trusted as a source of truth
• Build clean, well-modeled datasets to enable self-service analytics
• Support quarterly Fair Trade reporting, including sales data extraction and enrichment (country-of-origin and royalty attributes)

Requirements

• 6+ years experience in analytics engineering, data analytics, or BI
• Strong hands-on skills in SQL, dbt, Python, and Tableau
• Experience with cloud data platforms; Databricks strongly preferred
• Proven ability to own analytics systems from ingestion through executive dashboards

Nice-to-Haves / Additional Experience

• Experience supporting CPG, retail, supply chain, or manufacturing analytics
• Handling imperfect data and evolving business processes
• Experience with Azure and GCP (e.g., Blob Storage, Data Factory, BigQuery)
• Experience with POS data, retailer APIs, and NetSuite
• Familiarity with MRP, demand planning, or inventory management
• Experience operating at high volume dataset scale