Data Engineer - Supply Chain

We are building an AI-enabled supply chain that senses, predicts, prescribes, and acts. The Data Engineer plays a critical role in enabling this vision by designing, building, and operating enterprise-grade data pipelines and analytical data products that power advanced analytics, optimization, automation, and agentic AI solutions across the Supply Chain organization.

This role focuses on production-ready data engineering-ensuring data is reliable, governed, scalable, and fit for decisioning. The Data Engineer partners closely with Data Science, AI Engineering, Automation, and Platform teams to deliver high-quality data assets embedded into operational workflows.

Responsibilities include but not limited to:

• Design, build, and maintain scalable batch and near-real-time data pipelines supporting supply chain analytics and AI use cases

• Ingest, transform, and curate data from enterprise and operational systems (ERP, planning, logistics, manufacturing, execution platforms)

• Develop and maintain analytical data models and feature-ready datasets to support data science, optimization, and agentic AI workflows

• Implement data quality validation, monitoring, and alerting to ensure trust and reliability of downstream analytics

• Optimize data pipelines and storage for performance, cost, and scalability

• Partner with data scientists and AI engineers to support model training, scoring, and deployment needs

• Establish and follow best practices for data modeling, naming conventions, version control, and documentation

• Ensure data solutions comply with enterprise standards for security, privacy, lineage, and governance

• Support production operations, including incident investigation and root cause analysis related to data issues

Basic Qualifications:

• Bachelor’s in Computer Science, Information Systems, or a related field required

• 8+ years of professional experience in data engineering, analytics engineering, or data platform development

• Strong proficiency in Python and SQL for data transformation and pipeline development

• Experience designing and maintaining production-grade data pipelines and analytical data models

• Hands-on experience with modern data platforms such as Databricks, Spark, Snowflake, or equivalent

• Solid understanding of data quality, validation, and monitoring concepts

• Experience working with structured and semi-structured data at scale

• Proven ability to own production data pipelines end-to-end (design → deployment → monitoring → incident response)

• Demonstrated ability to operate independently, drive technical decisions, and deliver solutions in ambiguous environments with minimal oversight

• Ability to collaborate effectively with analytics, AI, and software engineering teams

Preferred Qualifications:

• Master’s Degree

• Experience supporting machine learning or advanced analytics pipelines, including feature engineering and model scoring data

• Experience with orchestration tools, CI/CD, and version control for data pipelines

• Familiarity with streaming or event-driven data architectures

• Experience working with supply chain, operations, manufacturing, or ERP data

• Knowledge of data governance, metadata management, and lineage tools

• Experience supporting BI or downstream analytics tools (e.g., Power BI) and enterprise data platforms (e.g. Palantir Foundry)