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Jellyfish Platform BI Engineer C2C in Minneapolis, MN

Job in Minneapolis, Hennepin County, Minnesota, 55400, USA
Listing for: Tech Mirrors
Full Time position
Listed on 2026-08-30
Job specializations:
  • IT/Tech
    SRE/Site Reliability, AI Engineer (Applied/Software), Data Engineering
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Position: Jellyfish Platform BI Engineer C2C roles in Minneapolis, MN

Role:
Jellyfish BI Engineer

(Engineering Intelligence Lead – Jellyfish / Delivery Observability)

Location:

Minneapolis, MN – Onsite

Experience

Required:

6–8 Years

Role Summary

Ownthe Jellyfish platform, implementation and operation of engineering intelligence and delivery observability.

The role will enable visibility into delivery lifecycle performance, engineering productivity, and workflow efficiency across AI initiatives.

This role is expected to immediately take over tooling ownership and partner with product, engineering, and AI teams to operationalize insights.

Key Responsibilities
  • Lead onboarding, configuration, and operationalization of Jellyfish platform.
  • Provide end-to-end visibility into delivery lifecycle and work orchestration.
  • Enable tracking of:
    • Engineering productivity
    • Work throughput and cycle time
    • Delivery bottlenecks and inefficiencies
  • Integrate Jellyfish with tools such as:
    • Azure Dev Ops (ADO)
    • Git Hub
    • Jira (future target)
  • Design dashboards and reporting for:
    • Leadership visibility
    • Delivery governance
  • Collaborate with:
    • AI DLC (Delivery Lifecycle) teams
    • App Ops / Observability teams
  • Enable data-driven decision making for engineering leadership.
  • Support scaling of the tooling ecosystem as additional tools are onboarded.
Required Skills
  • Strong experience with Jellyfish or similar engineering intelligence platforms.
  • Experience with SDLC tools integration (Git Hub, ADO, Jira).
  • Understanding of:
    • Agile delivery metrics
    • Software engineering lifecycle
    • Experience building reporting dashboards and analytics frameworks.
  • Strong stakeholder management skills.
Preferred Skills
  • Exposure to AI/ML development lifecycle (AI DLC).
  • Experience in observability and app performance measurement.
  • Familiarity with engineering productivity metrics frameworks.
Profile Expectation (Critical per Customer)
  • Hands-on and immediately deployable.
  • Capable of working directly with product and engineering teams.
  • Able to operate in high-pressure, fast-moving environments.

Skills:

Digital:
Microsoft Azure, Git Hub Enterprise

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