Platform Engineer - DataOps

Hollstadt Consulting; Arden Hills (MN); On-site; USD 63,000 - 65,000; Full time

Job summary

Hollstadt Consulting in Arden Hills, MN seeks a Platform (DataOps) Engineer to design and build automation, ingestion frameworks, CI/CD capabilities, and platform tooling for the Enterprise Data Platform. You will partner with Data Architects, Data Engineers, and product teams to enhance developer experience, reliability, and data delivery at scale.

This contract-to-hire role emphasizes platform automation, scalable solutions, and collaboration across engineering teams.

Qualifications

• Strong Python development and automation.
• Experience designing and supporting CI/CD pipelines.
• Experience with data ingestion/ETL/ELT processes.
• Automation solutions using APIs and scripting.
• Experience with cloud-hosted platforms and services.
• Troubleshooting and root-cause analysis skills.
• Strong collaboration and communication skills.

Responsibilities

• Design, develop, and maintain platform automation capabilities using Python, SQL, APIs, and CLI tools.
• Build reusable services and tooling to improve reliability and scalability of the Enterprise Data Platform.
• Design and implement CI/CD pipelines for automated testing, deployment, and operations.
• Develop data ingestion frameworks to onboard and move data across the platform.
• Create monitoring and observability solutions to improve platform reliability.
• Partner with Data Engineers and Data Architects to address platform gaps with scalable solutions.
• Contribute to platform engineering standards and best practices.
• Participate in MVP initiatives to evaluate new platform capabilities.
• Improve scalability, performance, and security through automation.
• Develop reporting to provide visibility into platform adoption and engineering effectiveness.

Skills

Python

CI/CD

Data ingestion/ETL

APIs scripting

Cloud platforms

Troubleshooting

Collaboration

Tools

Terraform

Snowflake

Databricks

Job description

Rate: $45.68- $47.25/hour W2 dependent on skills and qualifications

Work Authorization: This is a contract-to-hire opportunity. Candidates must be authorized to work in the United States and be eligible to convert to direct employment without current or future employer sponsorship.

Summary

The Platform (DataOps) Engineer designs and builds automation, ingestion frameworks, CI/CD capabilities, and platform tooling that enable the Enterprise Data Platform. This role partners with Data Architects, Data Engineers, and Product Teams to improve developer experience, platform reliability, and data delivery at scale.

Technical Platform Engineering

• Design, develop, and maintain platform automation capabilities using Python, SQL, APIs, and command-line tools.
• Build reusable services, frameworks, utilities, and tooling that improve the reliability, scalability, and efficiency of the Enterprise Data Platform.
• Design and implement CI/CD pipelines to automate testing, deployment, configuration, and operational processes.
• Develop and enhance data ingestion frameworks to support onboarding and movement of data across the platform.
• Create monitoring, observability, and operational intelligence solutions that improve platform reliability and reduce manual effort.
• Partner with Data Engineers and Data Architects to identify platform gaps and implement scalable technical solutions.
• Contribute to platform engineering standards, best practices, and development patterns.
• Participate in proof-of-concept and MVP initiatives that evaluate new platform capabilities and technologies.
• Improve platform scalability, performance, security, and operational efficiency through automation and engineering solutions.
• Develop reporting and insights that provide visibility into platform adoption, utilization, reliability, and engineering effectiveness.

Required Skills

• Strong proficiency in Python development and automation.
• Experience designing, building, and supporting CI/CD pipelines.
• Experience with data ingestion, ETL/ELT processes, or data pipeline frameworks.
• Experience developing automation solutions using APIs and scripting.
• Experience working with cloud-hosted platforms and services.
• Experience troubleshooting technical issues and performing root cause analysis.
• Strong collaboration and communication skills.

Preferred Skills

• Experience with Snowflake, Databricks, or similar cloud data platforms.
• Experience with Azure cloud services.
• Experience with Fivetran or similar ingestion technologies.
• Knowledge of Infrastructure as Code (Terraform, Bicep, ARM Templates, etc.).
• Experience implementing monitoring, alerting, and observability solutions.
• Experience with cloud cost monitoring and optimization.