Engineer, Staff Data

Independent Purchasing Cooperative•Pinecrest, FL

7d•Onsite

About The Position

IPC is seeking a highly motivated Staff Data Engineer to be responsible 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.

Requirements

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.
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.

Nice To Haves

Master’s degree preferred.

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.