Data Platform Engineer-Solutions Delivery

Seaboard Corporation•Merriam, KS

7d•Onsite

About The Position

We have an exciting opportunity for a Data Platform Engineer at our Merriam, KS office. The Data Platform Engineer is the core builder on the Data Platform team within Solutions Delivery, focused on designing, building, and operationalizing data solutions, primarily on Microsoft Fabric. This role is build-first: up to 80% of time is hands-on build — designing and shipping data pipelines, lakehouses, semantic models, APIs, and integrations that power Seaboard's AI and analytics capabilities. The remaining 20% is split between orchestrating delivery (10%) and defining the technical standards and patterns that govern the team's platform work (10%). This role sits at the intersection of data engineering, API development, and platform operations. The right candidate is an engineer who brings deep Microsoft Fabric expertise, writes clean and maintainable code, and understands that reliable data pipelines and well-designed APIs are as much a product as any application.

Requirements

Four + years of experience in data integrations, data modeling, or closely related data engineering work.
Hands-on experience building data solutions on Microsoft Fabric or an equivalent modern cloud data platform.
Hands-on proficiency with PySpark, SQL, and Python for data engineering work at production scale.
Experience designing, building, and consuming APIs — including and debugging integration failures.
Experience with data warehouse or lake house design patterns: medallion architecture, data modeling, partitioning, and incremental load strategies.
Track record shipping production data pipelines and integrations, including within the past 12 months. This is a build-first role.
Demonstrated ability to work independently on complex, ambiguous data problems and iterate toward a working solution without close supervision.
Strong communication skills — able to explain data concepts, design decisions, and trade-offs to both technical peers and non-technical business stakeholders.
Experience working across the full data solution lifecycle: design, build, test, monitor, and operate.
Understanding business operations and the ability to connect data architecture decisions to business outcomes.

Nice To Haves

Direct experience with Microsoft Fabric workloads: Lakehouse, Data Warehouse, Dataflows Gen2, Notebooks, Pipelines, and/or Real-time Intelligence.
Experience building and maintaining semantic models.
Familiarity with AI/data platforms used in enterprise delivery.
Experience with Azure API Management, Azure Functions, or other Azure integration services.
Experience with source control, CI/CD practices, and DevOps pipelines applied to data engineering work.
Background in manufacturing, agriculture, food & beverage, or other process-driven industries.
Degree in Computer Science, Information Systems, Data Engineering, or a related field.

Responsibilities

Design, build, test, and deliver data pipelines, data transformations, lakehouses, data warehouses, and semantic models in Microsoft Fabric using Dataflows Gen2, Notebooks (PySpark, SQL), and Fabric Pipelines.
Ingest, transform, and serve data across the business — building the OneLake structures and medallion architecture patterns that make data reliably available for reporting, AI features, and downstream applications.
Build, consume, and maintain APIs as appropriate — designing clear contracts, implementing endpoints, and integrating with internal systems and external vendors to ensure data flows where it is needed.
Develop and maintain semantic models, ensuring data accuracy, performance, and reusability for reporting and AI-driven use cases across the business.
Partner with Forward Deployed Engineers (FDEs) and business stakeholders to understand data requirements and iterate rapidly in tight feedback loops.
Implement monitoring, alerting, and operational runbooks for platform components; partner with Application Support to confirm data assets and integrations are operationally ready before go-live.
Stay current on Microsoft Fabric capabilities — new workloads, performance features, governance tooling — and pull proven patterns into the team’s work as they mature.
Participate in team standups, planning sessions, and delivery ceremonies; surface data dependencies, blockers, and capacity constraints proactively so they can be resolved before they slow delivery.
Coordinate with FDEs, Architecture, and external partners to align on data contracts, API specifications, and integration patterns before build begins, reducing rework and integration friction.
Clarify data requirements and priority when the scope is ambiguous: pull the right stakeholders into the conversation, confirm direction, and keep build work moving.
Define and document reusable patterns for data pipeline design, semantic model development, and API integration in the Seaboard context, so the team converges on what works rather than rediscovering it on each initiative.
Conduct data and API design reviews to raise quality, catch performance or consistency issues early, and reduce long-term maintenance burden.
Maintain documentation for data assets, schemas, and integration contracts so other engineers and business users can consume them without friction; retire patterns that no longer hold.