Technical Product Manager, Data Platform (Hybrid)

Early Warning; Chicago (IL); Hybrid; USD 101,000 - 152,000; Full time

Benefits offered by this job

Healthcare Coverage

401(k) Match

Paid Time Off

Parental Leave

Maven Family Planning

Discretionary incentive

Job summary

Early Warning is seeking a Technical Product Manager on the Data & AI team to define and deliver the next generation of enterprise data platform capabilities. You will own the vision, roadmap, and execution of self‑service data workflows used by data engineers, analytics engineers, software engineers, and data scientists.

Collaborating with Data Engineering, Platform Engineering, Analytics, Architecture, Governance, Security, and business stakeholders, you will translate needs into scalable

Qualifications

• Bachelor's degree in STEM, CS, IS, Engineering, or related field.
• 5+ years in Product/Data Platform/Product Management.
• 3+ years working with data/engineering teams.
• Experience delivering internal platforms or enterprise tech capabilities.
• Strong data platform knowledge: pipelines, data lakes/warehouses, governance.
• Proficient in SQL and Agile (Jira).

Responsibilities

• Execute the product roadmap for enterprise data platform capabilities (in ingestion, governance, observability, self-service workflows).
• Collaborate with Data Eng, Platform Eng, Analytics, Architecture, Security, and Governance teams.
• Translate user needs into platform requirements and product enhancements.
• Define and prioritize requirements, user stories, and technical capabilities.
• Establish metrics and measure adoption, reliability, and business impact.

Skills

Stakeholder management

Excellent communication

SQL

Agile methodologies

Education

Bachelor's degree in STEM or related field

Tools

Jira

Job description

Early Warning is seeking a Technical Product Manager on the Data & AI team to define and deliver the next generation of enterprise data platform capabilities. You will own the vision, roadmap, and execution of self‑service data workflows used by data engineers, analytics engineers, software engineers, and data scientists.

Collaborating with Data Engineering, Platform Engineering, Analytics, Architecture, Governance, Security, and business stakeholders, you will translate needs into scalable