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Lead – Jellyfish Delivery Observability
Job Location:
Job Location:
Minneapolis, MN - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
28 July 2026 (30+ days ago)
Posted:
Application Deadline:
25 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Title: Engineering Intelligence Lead - Jellyfish / Delivery Observability
Location: Minneapolis MN
Experience: 6-8 Years
Job Summary
We are seeking an experienced Engineering Intelligence Lead to own and operationalize the Jellyfish Engineering Intelligence platform while driving engineering productivity delivery observability and SDLC analytics across enterprise engineering teams. The ideal candidate will have hands-on experience with Jellyfish Azure DevOps GitHub Agile delivery metrics engineering analytics and observability platforms. This role partners closely with Product Engineering AI and Operations teams to enable data-driven engineering decisions and continuous delivery improvements.
Required Skills
Engineering Intelligence & Delivery Analytics
- Jellyfish Platform
- Engineering Intelligence
- Delivery Observability
- Engineering Productivity Metrics
- SDLC Analytics
- Software Delivery Analytics
- Delivery Governance
- Workflow Analytics
- Engineering Performance Measurement
SDLC & DevOps Tools
- Azure DevOps (ADO)
- GitHub Enterprise
- GitHub
- Jira
- CI/CD Pipelines
- Software Development Lifecycle (SDLC)
- Agile Delivery
- Scrum
- Kanban
Reporting & Analytics
- Dashboard Development
- KPI Reporting
- Executive Dashboards
- Delivery Metrics
- Cycle Time Analysis
- Lead Time Analysis
- Throughput Metrics
- Bottleneck Analysis
- Flow Metrics
- Engineering Insights
- Data Visualization
Observability
- Delivery Observability
- Application Observability
- Engineering Observability
- Platform Monitoring
- Performance Measurement
- Operational Analytics
AI & Engineering Platforms
- AI Development Lifecycle (AI DLC)
- AI Engineering
- Engineering Workflow Automation
- Engineering Toolchain Integration
Integration
- Azure DevOps Integration
- GitHub Integration
- Jira Integration
- API Integrations
- Data Integration
- Enterprise Tool Integration
Soft Skills
- Stakeholder Management
- Engineering Leadership
- Cross-functional Collaboration
- Product Partnership
- Communication Skills
- Problem Solving
- Analytical Thinking
- Process Improvement
Key Responsibilities
- Lead the implementation onboarding configuration and operational management of the Jellyfish Engineering Intelligence platform
- Build delivery observability capabilities to provide visibility into engineering productivity workflow efficiency and software delivery performance
- Integrate Jellyfish with Azure DevOps GitHub Jira and other enterprise SDLC tools
- Develop executive dashboards and engineering analytics for leadership reporting and delivery governance
- Track engineering KPIs including throughput cycle time lead time delivery bottlenecks and engineering efficiency
- Partner with Product Engineering AI Delivery Lifecycle (AI DLC) and AppOps teams to improve engineering execution
- Drive data-driven decision making by providing actionable delivery insights and performance metrics
- Support the expansion of the engineering tooling ecosystem as additional platforms are onboarded
- Collaborate with stakeholders to establish engineering productivity measurement frameworks and best practices
- Monitor platform performance ensure data quality and continuously optimize reporting capabilities
Preferred Qualifications
- Hands-on experience with Jellyfish Engineering Intelligence platform
- Experience with AI/ML Development Lifecycle (AI DLC)
- Knowledge of engineering productivity frameworks (DORA Metrics Flow Metrics)
- Experience with application observability and engineering analytics platforms
- Experience working in enterprise Agile and DevOps environments
- Strong understanding of software engineering lifecycle and delivery governance
