Build and maintain end-to-end data pipelines (ingestion through curated, decision-ready datasets) Develop and extend semantic/ontology layers that model supply chain entities, relationships, and business logic for planning use cases Design and implement orchestration frameworks that connect data pipelines, analytical models, and decision workflows across planning processes Apply structured problem solving to break down complex, ambiguous planning challenges into scalable technical solutions Write production-grade code (e.g., Python, SQL) to process large structured and unstructured datasets Implement orchestration, scheduling, monitoring, and error handling aligned with planning cycles (e.g., demand, supply, IBP) Integrate data from Snowflake, Databricks, APIs, and enterprise systems into unified data platforms Ensure data quality, consistency, and governance, particularly as it relates to shared business objects and planning logic Translate business objectives into scalable solution architectures, from prototype through production deployment Deliver decision intelligence solutions that transform data into operational workflows and planning decisions Collaborate with cross-functional teams (business, data science, IT) to align on data models, workflows, and outcomes Bring a continuous learning mindset, adapting to new platforms, tools, and evolving supply chain needs Bachelor's or Master's in Data Science, Computer Science, Engineering, or related field Strong experience in data engineering and pipeline development Proficiency in Python and SQL Experience with ETL/ELT and orchestration frameworks Experience with modern data platforms (Snowflake, Databricks, or similar) Understanding of data modeling, semantics, and governance principles Experience designing systems that support business workflows and decision-making processes Experience with Palantir Foundry ontology, pipelines, and operational workflows Familiarity with semantic modeling / knowledge graph concepts / enterprise ontology design Supply chain domain experience across end-to-end planning (demand, supply, inventory, IBP) Exposure to AI/ML pipelines or decision intelligence platforms Experience supporting scenario planning or optimization-based solutions
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