Staff Data Product Manager

Why Michels?

We are consistently ranked among the top 10% of Engineering News-Record’s Top 400 Contractors
Our steady, strategic growth revolves around a commitment to quality
We are family owned and operated
We invest an average of $5,000 per employee on training each year
We reward hard work and dedication with limitless opportunities
We believe it is everyone’s responsibility to promote safety, regardless of job titles.
We offer a comprehensive benefits program including (depending on your positions and location you may participate in a different benefit plan):
Health, Dental, Life, Flexible Spending Accounts, Health Savings Account, Short Term and Long-Term Disability Insurance, 401(k) plan, Legal Plan, and Identity Theft and Monitoring Plan

Key Responsibilities

• Engage stakeholders across business and technology to surface pain points, clarify needs, and uncover where better data improves decisions.
• Prioritize the highest-value opportunities, deciding which platform capabilities are worth enabling and which products are worth building and why to maximize business value as the platform is established.
• Define curated, intuitive data products, including tables and semantic models, across all domains.
• Translate business needs into actionable stories and acceptance criteria, then guide engineering through development, testing, and delivery.
• Uphold quality and consistency standards so the data assets are documented, dependable, and suited for self-serve consumption.
• Measure adoption and outcomes, using those signals to validate value and guide what comes next.

Qualifications

• Bachelor's degree in Business, Technology, Engineering, Computer Science, a quantitative field, or equivalent practical experience.
• 7+ years of experience in data product management, guiding cross-functional teams to deliver data products on a scalable cloud data platform for enterprise consumption.
• Proven experience defining product roadmaps, requirements, user stories, and success metrics while guiding products or platforms through the full lifecycle from discovery through adoption.
• Strong understanding of data management concepts including data governance, metadata, data quality, data lineage, and the principles required to build trusted and reusable enterprise data assets.
• Exposure to leading cloud data platforms such as Snowflake, Databricks, Microsoft Fabric, BigQuery, or similar technologies.