Engineer, Staff Data

At Independent Purchasing Cooperative (IPC), we are more than just a supply chain services provider—we're the strategic sourcing partner behind one of the world’s most recognized brands: Subway®. As a member-owned organization, we are driven by our commitment to serve the franchisees who own and operate Subway® restaurants across North America, Canada, Puerto Rico, and the U.S. Virgin Islands.

Headquartered in Miami, FL, we were founded in 1996 with a mission to help franchisees be more profitable and competitive by delivering exceptional value through supply chain solutions, contract negotiation, technology initiatives, and industry expertise.

At IPC, you'll find a supportive and inclusive environment that fosters personal growth, professional development, and a healthy work-life balance. Whether you're a seasoned supply chain professional or just beginning your career journey, IPC offers opportunities to make a meaningful impact!

IPC is seeking a highly motivated Staff Data Engineer to be responsible for for bringing agentic and AI-assisted workflows into IPC’s data engineering practice, and for the hands-on design, delivery, and support of the data platforms behind supply chain operations serving approximately 21,000 Subway restaurants throughout Canada, the United States, and Latin America. This role designs, evaluates, and productionizes AI-assisted workflows across the data lifecycle, establishes the guardrails and evaluation standards that govern their use, and raises the capability of the wider data engineering team so those practices become a durable part of how work gets done. The role also carries hands-on delivery across two strategic platform initiatives, Microsoft Fabric and Palantir Foundry, and defines how data, lineage, and governance move consistently between them. In this role, you are expected to operate as a technical leader, influencing outcomes through design, code review, mentorship, and enablement across the data engineering team, reporting to the Director of Information and Data Services.

Essential Duties and Responsibilities

The essential duties and responsibilities, knowledge, skills, and abilities listed below are required to be successful in this position. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential duties and responsibilities.

• Design, prototype, and productionize agentic and AI-assisted workflows that improve data engineering throughput, quality, and cycle time.
• Establish evaluation methods and success criteria for AI-assisted workflows, so their impact can be measured.
• Define technical guardrails for AI tooling that touches organizational data, including human review checkpoints, access boundaries, audit logging, and rollback paths.
• Serve as the technical authority and internal enablement lead for applied AI within the data engineering team.
• Deliver hands-on engineering across Microsoft Fabric and Palantir Foundry initiatives, including ingestion, transformation, semantic modeling, and orchestration.
• Partner with Security, Compliance, and Data Governance to keep AI-assisted workflows within policy for data classification, access control, retention, and auditability.
• Define how workloads, lineage, and governance are divided and reconciled between Microsoft Fabric and Palantir Foundry.
• Provide technical design review, code review, and mentorship that raises engineering standards across the data engineering team.•All other duties as reasonably assigned.

Knowledge, Skills, and Abilities

Agentic & AI-Assisted Engineering

• Design and implement agentic workflows for pipeline scaffolding, schema and data contract validation, test generation, documentation, and incident triage.
• Build retrieval, structured extraction, and tool-using patterns against governed enterprise data sources.
• Maintain reference implementations, tooling libraries, and reusable templates that other engineers can extend without direct support.

AI Guardrails & Data Governance

• Define human-in-the-loop checkpoints, blast-radius limits, and rollback procedures for workflows with write access to production systems.
• Establish data access boundaries, classification handling, and audit logging standards for AI tooling.
• Apply data quality checks, lineage capture, and monitoring to AI-generated and AI-assisted outputs.
• Ensure compliance with applicable privacy, security, and data retention requirements across multiple international jurisdictions.

Data Engineering & Platform Delivery

• Build and support enterprise data pipelines and integration services across ingestion, transformation, validation, and publishing.
• Deliver hands-on engineering within Microsoft Fabric, including Lakehouse design, pipelines, and semantic models.
• Deliver hands-on engineering within Palantir Foundry, including pipelines, ontology objects, and operational workflows.
• Drive automation, automated testing, and CI/CD practices across data engineering codebases.

Enablement & Practice Leadership

• Run working sessions, office hours, and technical walkthroughs that move the team from ad-hoc AI usage toward governed, repeatable workflows.
• Publish patterns, anti-patterns, and onboarding material so new capability spreads without dependence on a single person.
• Coach engineers through design review and code review, with particular attention to AI-adjacent work.
• Build starter repositories & templates lowering cost of adopting engineering practices.

Cross-Platform Architecture & Interoperability

• Define where each workload belongs across Microsoft Fabric, Palantir Foundry, and adjacent Azure data services.
• Ensure lineage, metadata, and governance standards are applied consistently.
• Design integration patterns across platform boundaries, ERP systems, supplier platforms, and external data providers.
• Keep agentic and AI-assisted patterns portable rather than locked to a single vendor’s tooling.

Collaboration & Technical Influence

• Partner with analytics, product, and business stakeholders to identify where AI-assisted approaches create leverage and where they add risk without payoff.
• Advise engineering leadership on tooling evaluation, build-versus-buy decisions, and capability roadmap.
• Represent the data engineering team in technical discussions with Microsoft, Palantir, and other technology partners.

Competencies

• Action Oriented: Takes on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm while maintaining humble professionalism
• Customer Focus: Building strong franchisee experience through customer and vendor relationships that delivers franchisee-centric solutions
• Ensures Accountability: Holds self and others accountable to meet commitments, acts with a clear sense of ownership, takes personal responsibility for decisions, actions, and failures
• Collaborates: Builds partnerships and works collaboratively with others to meet shared objectives while gaining trust and support of others
• Communicates Effectively: Develops and delivers a clear message in a variety of communication settings, attentively listens to others, and adjusts their own style
• Decision Quality: Makes good and timely decisions that keep the organization moving forward
• Plans and Aligns: Plans and prioritizes work to meet commitments aligned with organizational goals
• Resourceful: Secures and deploys resources effectively and efficiently
• Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels
• Tech Savvy: Anticipates and adopts innovations in business-building digital and technology applications

Qualifications & Experience

• 7+ years of progressive experience in data engineering, software engineering, or a closely related technical discipline.
• Bachelor’s or equivalent degree in relevant discipline such as Computer Science, Information Systems or Engineering, Data Science. Master’s degree preferred.
• 3+ years’ experience building with large language models beyond casual usage, such as agentic or tool-using systems, retrieval architectures, structured extraction pipelines, or evaluation harnesses.
• 7+ years’ experience with distributed data processing and modern pipeline architecture, including Spark, SQL at scale, and orchestration frameworks.
• 3+ years’ experience supporting supply chain, procurement, logistics, distribution, or retail operations environments preferred.
• 5+ years’ experience mentoring engineers, driving adoption of new engineering practices, or leading technical enablement across a team.

Technical Expertise Required:

• Microsoft Fabric (OneLake, Lakehouse, Data Factory pipelines, semantic models)
• Modern Data Warehousing and Lakehouse Architecture
• Python, SQL, and Spark
• Agentic AI applied to data engineering
• Agentic Frameworks, Tool Use, and LLM Orchestration
• ETL/ELT Architecture and Data Contracts
• LLM Evaluation, Observability, and Guardrail Design
• API and Systems Integration
• Palantir Foundry, AIP, Ontology design, management and maintenance
• Git, CI/CD, Automated Testing, and Infrastructure as Code
• Experience in Azure Cloud and Azure Data Services.

Leadership Responsibility: No direct reports. Holds technical decision authority for the data engineering team in the following areas: AI-assisted and agentic workflow design, engineering standards and tooling, and technical design review for data platform work. Designs in these areas require this role's approval before implementation. Broader prioritization and staffing decisions remain with the Director of Information and Data Services.

Travel: This job does not require international travel. Occasionally, local travel within driving distance, and overnight domestic travel may be required.

Work Conditions: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. This job operates in a professional office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers, and filing cabinets. While performing the duties of this job, the employee is regularly sitting for long periods of time. A detailed description of these physical requirements is available upon request. Compliant with the ADA, reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions of the job.

This is a full-time position. Standard office hours of Monday through Friday, 8:30 AM to 5:00 PM EST. This position may require additional work hours outside these work hours, including weekends, to complete job requirements.

Independent Purchasing Cooperative (IPC) provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

Disclaimer: The above job description is meant to describe the general nature and level of work being performed; it is not intended to be an exhaustive list of all responsibilities, duties, and skills required for the position. Team Members may be required to perform other duties as requested by their leader(s) in compliance with Federal and State laws.