Platform Engineer

Note:

If you apply for a role at Hershey through our career’s website, we may use technologies that use automation to filter your candidacy based on objective criteria. We also use AI-enabled tools that help us facilitate the selection of our future Hershey talent. These tools may help with activities such as matching and scoring candidates to roles based on requirements and scheduling interviews.

These systems process only the information you provide in your application, including your resume, work history, education, and responses to screening questions. While these technologies assist with certain steps in our recruitment process and may provide recommendations, all final decisions, including those affecting whether candidates advance to subsequent stages in the applicant process, are made by our talent acquisition teams with meaningful human review and independent judgment.

Depending on your location and the specific role you apply for, additional disclosures about our use of AI in recruitment may be provided to you separately.

Platform Engineer

The Platform Engineer, Data & Analytics Platforms runs and continuously improves the enterprise data and analytics platforms that power Hershey’s data products. This role focuses on platform operations and enablement—standardizing environments, automating delivery, improving reliability and observability, and reducing time-to-value for Data Product teams across development, test, and production.

The Data Platform Engineer partners with Senior Data Engineers, Solution Architects, the Cloud COE, and Security to define guardrails and operating standards, deliver self-service tooling, and keep the platform cost-effective, secure, observable, reliable, and scalable.

This role supports Hershey’s enterprise data strategy by operating and enabling a trusted, governed data platform  platform team turns one-off solutions into reusable templates, guardrails, and automated workflows—improving reliability, cost transparency, and developer experience so Data Product teams can deliver high-quality data products faster.

• Data Platform Components
• Own and operate core data platform components (with emphasis on Databricks and supporting Azure services) across development, test, and production.
• Build and maintain CI/CD and environment standardization using Azure Dev Ops and infrastructure-as-code (e.g., Terraform) to improve consistency, security, and delivery speed.
• Implement observability (logging, monitoring, alerting, dashboards) and maintain operational runbooks to enable proactive detection and faster recovery.
• Implement identity/access controls, secrets management, and configuration standards in partnership with the Cloud COE and Security.
• Plan and execute platform releases and upgrades (libraries, runtimes, clusters/pools) and coordinate change communications to minimize disruption for Data Product teams.
• Machine Learning Operations (MLOps)
• Enable MLOps capabilities (e.g., MLflow standards, deployment patterns, automation) in partnership with Data Science and engineering teams.
• Governance, Quality & Operations
• Implement governance, security, and compliance standards through platform guardrails (policies, templates, controls) and clear documentation.
• Support Fin Ops by monitoring usage, identifying optimization opportunities (clusters, jobs, storage), and improving cost transparency (e.g., tagging and showback/chargeback inputs).
• Monitor platform health, resolve incidents, perform root-cause analysis, and drive problem management to improve stability and meet agreed service levels.
• Define, track, and report operational KPIs (availability, performance, deployment frequency, MTTR) and drive continuous improvement through automation and standardization.
• Provide operational support during standard business hours, with planned maintenance windows and documented support processes (no on-call rotation).
• Collaboration Across Domains
• Enable Data Product teams with self-service tooling, reusable patterns/templates, and onboarding/training; manage a clear intake and prioritization…