Sr Platform Engineer
hersheysDallas (TX)
About the role
Overview:
In this role you build and operate end-to-end data pipelines and platform components to power Hershey’s enterprise data products. You will work as an autonomous contributor across development, test, and production environments, turning requirements into scalable, reliable solutions. You’ll create reusable templates and automation to improve reliability, observability, and developer experience. You’ll collaborate with data engineers, architects, security, and data science teams to keep the data platform secure and scalable. This is a chance to enable impactful data-driven decisions at scale and shape Hershey’s data capabilities. Compensation / Benefits Medical, dental, and vision coverage Wellness programs 401(k) with company match Paid time off and holidays Flexible ways of working where applicable Career development programs and internal mobility
Responsibilities:
Design, build, deploy, and support data pipelines, data models, and platform components using Databricks and Azure services Translate business requirements into production-ready solutions across development, test, and production environments Improve performance, reliability, and observability of pipelines, clusters, and storage with cost awareness Implement monitoring, dashboards, data quality controls, and runbooks; track metrics like availability and deployment frequency Troubleshoot and resolve data and platform issues; conduct root-cause analysis and implement lasting improvements Strengthen governance, security, and compliance through policies, access controls, and guardrails; enable MLOps (MLflow) in collaboration with teams
Key requirements:
3+ years of experience in data engineering, platform engineering, or related field Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field Experience with Databricks and Azure data platform services including environment management and secrets management Proficiency in Python and SQL; familiarity with APIs, scripting, and Git Experience implementing CI/CD pipelines in Azure DevOps and release management practices Knowledge of monitoring, incident management, data quality, and root-cause analysis Infrastructure-as-code experience (Terraform preferred); familiarity with MLflow and MLOps is a plus Cross-functional collaboration Problem-solving and initiative Strong communication and ownership Databricks Azure data platform services Python
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.