Data Product Manager - Modernization & Data Strategy (Remote)

RE/SPEC Inc.; Saint Paul (MN); Hybrid; USD 110,000 - 150,000; Full time

Job summary

RESPEC is seeking an experienced Data Product Manager to lead a major state modernization initiative for MNIT and DCYF. You will transform core human services data into scalable, governed assets powering decision-makers and frontline staff.

You will bridge executive stakeholders, data engineering, and analytics teams, guiding migration from legacy mainframes to cloud data lakes and lakehouse architectures, with governance and ethical data use at the core.

Qualifications

• 4+ years of professional data experience across data management, data engineering, analytics, or product management.
• Strong SQL, ETL/ELT, data warehousing, and modern lakehouse architectures.
• Experience leading data/digital products through full lifecycle with clear technical specs.
• Excellent verbal and written communication for executive audiences.

Responsibilities

• Product Strategy & Roadmap: define vision, prioritize backlogs, link data with state outcomes.
• Modernization & Lifecycle Delivery: migrate pipelines to lakehouse platforms with data lineage.
• Cross-Functional Collaboration: work with data engineering/science to build scalable pipelines.
• Stakeholder Enablement & Analytics: implement dashboards in Tableau, Power BI, Looker; measure adoption.
• Governance & Ethical Data Use: ensure privacy, governance, and regulatory compliance.
• Knowledge Transfer & Mentorship: lead training and documentation for long-term ops.

Skills

Data product management

Stakeholder management

Communication

Strategic thinking

Tools

Databricks

dbt

Tableau

Power BI

Looker

Google Analytics

Job description

RESPEC is seeking an experienced Data Product Manager to lead a major state modernization initiative for MNIT and DCYF. You will transform core human services data into scalable, governed assets powering decision-makers and frontline staff.

You will bridge executive stakeholders, data engineering, and analytics teams, guiding migration from legacy mainframes to cloud data lakes and lakehouse architectures, with governance and ethical data use at the core.