Data Platform Engineer II - Corporate Office (Austin, MN preferred)

Hormel Foods•Austin, MN

9d•Hybrid

About The Position

Are you passionate about building the tools, platforms, and engineering practices that power modern data and analytics capabilities at scale? As a Data Platform Engineer II, you will play a key role in advancing our Enterprise Data Foundation within Google Cloud Platform (GCP), supporting the ingestion, data, and orchestration layers that enterprise analytics and decision-making. This role is focused on the technologies, standards, automation, and developer processes that allow Data & Analytics teams to deliver solutions faster, more reliably, and with greater consistency. You will help drive the roadmap, adoption, and evolution of enterprise data and analytics tools and platforms, including a custom Python-based ingestion framework responsible for moving and processing data across the organization. Working closely with Data Engineering, Integration, Architecture, Infrastructure, Security, Governance, and Data Analytics teams, you will influence platform direction, improve developer productivity through automation and CI/CD capabilities, and help shape the future of our enterprise data ecosystem. This is an exciting opportunity to work at the intersection of platform engineering, cloud technologies, automation, and enterprise data strategy while helping shape the future of enterprise data and analytics capabilities across the company.

Requirements

Bachelor’s degree in computer science, MIS, engineering, or related field, and significant experience supporting enterprise data, analytics, and technology platforms.
7+ years of experience supporting or enabling enterprise data, analytics, ingestion, orchestration, engineering, DevOps, cloud, or related technology tools and platforms.
Experience establishing and advancing tool and platform roadmaps, release strategies and coordination, standards, operational practices, and vendor engagement activities for enterprise data and analytics tools.
Experience driving platform adoption, developer enablement, and engineering productivity through automation, documentation, self-service capabilities, and training.
Experience designing, implementing, and supporting CI/CD frameworks, deployment automation, source control practices, and software development (SDLC) standards.
Experience evaluating platform capabilities, defining technical standards, and influencing platform direction across multiple engineering teams.
Experience implementing developer enablement programs, technical documentation, onboarding frameworks, and self-service tooling.
Experience developing automation solutions using Python, SQL, scripting, or related technologies.
Proven ability to gather and evaluate technical requirements and translate them into scalable platform capabilities and engineering solutions.
Excellent written and verbal communication skills.
Strong organizational and time management skills.
Tested problem-solving and decision-making skills.
Strong pattern of initiative.
Highly developed interpersonal skills.
Demonstrated success working across multiple technical teams and influencing engineering practices without direct authority.
Applicants must not now, or at any time in the future, require sponsorship for a work visa.
Applicants must be authorized to work in the United States for any employer.

Nice To Haves

Experience supporting enterprise semantic layer, analytics, or AI tools and platforms.
Experience with Incorta, Apigee, custom Python-based ingestion frameworks, API integration technologies, and large-scale data ingestion solutions.
Experience working with Google Cloud Platform (GCP), including technologies such as BigQuery, Cloud Storage, Composer/Airflow, Pub/Sub, Dataflow, Dataproc, Artifact Registry, Kubernetes/GKE, Cloud Build, or related cloud-native platform services.
Experience designing and supporting CI/CD solutions using Azure DevOps, GitHub, GitHub Actions, Google Cloud Build, Jenkins, or similar technologies.
Experience defining SDLC standards, deployment governance, code management practices, and engineering controls.
Experience developing reusable frameworks, templates, automation solutions, and engineering accelerators.
Experience supporting enterprise Data & Analytics organizations and multiple engineering disciplines.

Responsibilities

Drive the roadmap, adoption, and continuous improvement of enterprise ingestion, data, and orchestration tools and platforms.
Partner with Data Engineering, Integration, Architecture, Infrastructure, Security, Governance, and Data Analytics teams to enable scalable, secure, and reliable platform capabilities.
Lead data and analytics tool and platform lifecycle activities including roadmap planning, releases, upgrades, vendor engagement, automation, and modernization initiatives.
Design, implement, and support CI/CD frameworks, deployment automation, and engineering standards that improve delivery speed, quality, and consistency.
Develop reusable tooling, templates, automation solutions, and self-service capabilities that enhance developer productivity and platform adoption.
Establish and evolve software development lifecycle (SDLC) standards, deployment governance, source control practices, and engineering best practices.
Support and enhance enterprise ingestion capabilities, including a custom Python-based ingestion framework and related platform technologies.
Evaluate emerging technologies and platform capabilities, providing recommendations that align with enterprise data and analytics strategy.
Create and maintain technical documentation, onboarding materials, training resources, runbooks, and operational standards.
Partner with delivery teams to improve tool and platform utilization, reduce operational friction, and accelerate solution delivery.
Implement and enhance tool and platform observability, monitoring, reliability, and operational support capabilities.
Collaborate with software vendors and external partners to support roadmap planning, platform enhancements, issue resolution, and adoption initiatives.
Serve as a technical leader and trusted advisor for enterprise data and analytics tooling, standards, automation, and developer enablement initiatives.