Remote Tech Product Manager – Cloud FinOps & Analytics

Optum

Eden Prairie (MN)

Hybrid

USD 92,000 - 164,000

Full time

14 days+

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Benefits offered by this job

Comprehensive benefits

Incentive programs

Equity stock purchase

401k contribution

Job summary

Optum is hiring a Technical Product Manager for Cloud FinOps Analytics & Optimization to drive cost optimization across cloud and on-prem workloads. You will translate consumption data into actionable recommendations, partner with engineering and application teams, and manage optimization programs to realization of savings.

The role emphasizes data-driven analysis, AI-assisted insights, and executive-ready reporting to inform leadership decisions.

Qualifications

4+ years of experience as a Technical Product Manager driving outcomes across cloud, SaaS platforms, infrastructure, or FinOps-related products.
2+ years of experience with cloud cost drivers, usage optimization levers, and value realization across Azure, AWS, GCP, Snowflake, Databricks, MongoDB, and data center environments.
2+ years of experience in data analytics related to cloud and on-prem optimization through metrics and reporting.
2+ years of experience with data visualization tools such as Power BI, Tableau, or Looker/Data Studio.
6+ months of experience building AI agents or leveraging AI-assisted tools for business or operational functions.
Experience with SQL scripting.
Experience with advanced Excel skills including Pivot Tables, VLOOKUP/XLOOKUP, INDEX-MATCH, conditional formulas, and data modeling.
Experience partnering with customers or application teams to drive adoption and behavior change.
Experience translating complex technical and financial data into clear, actionable recommendations.
Experience with backlog management, prioritization, and agile delivery methodologies.

Responsibilities

Analyze cloud and on-prem infrastructure spend across AWS, Azure, GCP, Snowflake, Databricks, MongoDB, and related platforms.
Identify and validate optimization opportunities including rightsizing, storage optimization, idle resource cleanup, database optimization, autoscaling, and workload modernization.
Quantify opportunity value, implementation effort, and realized savings.
Perform ad hoc analysis to support optimization programs and business decisions.
Develop data-driven recommendations that improve cloud efficiency and resource utilization.
Track optimization pipelines from identification through implementation and realization; partner with engineering and application teams to drive execution.
Monitor optimization results and identify additional opportunities for improvement; support prioritization based on business value.
Prepare executive-ready reports, scorecards, dashboards, and optimization summaries; track realized savings and adoption; support MBRs and QBRs.
Utilize AI tools and Copilots to improve analysis efficiency and opportunity discovery; develop repeatable analytical frameworks and reporting processes.