Position: Engineering Intelligence Lead (Jellyfish / Delivery Observability)

Experience Required

6-8 Years

Job Summary

We are seeking an experienced Engineering Intelligence Lead with hands-on expertise in Jellyfish Engineering Intelligence Platform Delivery Observability and Engineering Productivity Analytics. The ideal candidate will own the implementation configuration and operational management of the Jellyfish platform while enabling visibility into engineering productivity software delivery performance and SDLC metrics across enterprise technology initiatives.

This role will work closely with engineering product DevOps AI and leadership teams to deliver actionable insights through dashboards reporting and workflow analytics. The candidate should have experience integrating SDLC tools such as Azure DevOps (ADO) GitHub and Jira along with a strong understanding of Agile delivery metrics and engineering performance frameworks.

Key Responsibilities

Engineering Intelligence Platform

• Own the implementation configuration and administration of the Jellyfish Engineering Intelligence Platform.
• Lead onboarding of engineering teams onto the platform.
• Configure engineering metrics workflows and reporting dashboards.
• Maintain platform performance security and operational stability.

Delivery Observability

• Provide end-to-end visibility into the software delivery lifecycle.
• Monitor and analyze:
  • Engineering productivity
  • Development throughput
  • Cycle time
  • Lead time
  • Delivery velocity
  • Deployment frequency
  • Engineering bottlenecks
• Identify process inefficiencies and recommend improvements.

Tool Integration

• Integrate Jellyfish with enterprise SDLC tools including:
  • Azure DevOps (ADO)
  • GitHub Enterprise
  • Jira
  • CI/CD platforms
• Ensure accurate synchronization of engineering and delivery data.

Reporting & Analytics

• Design and develop executive dashboards and engineering scorecards.
• Build reports for:
  • Engineering Leadership
  • Product Management
  • Delivery Governance
  • Executive Stakeholders
• Provide actionable insights to improve software delivery performance.

Collaboration

• Partner with:
  • Engineering Teams
  • Product Managers
  • DevOps Teams
  • AI Delivery Lifecycle (AI DLC) Teams
  • Application Operations
  • Observability Teams
• Support engineering transformation initiatives.

Process Improvement

• Define engineering productivity KPIs.
• Establish delivery governance standards.
• Recommend improvements to Agile delivery processes.
• Drive adoption of engineering intelligence best practices.

Required Technical Skills

Engineering Intelligence

• Jellyfish Engineering Intelligence
• Engineering Productivity Analytics
• Delivery Observability
• SDLC Analytics
• Software Delivery Metrics

SDLC Tools

• Azure DevOps (ADO)
• GitHub Enterprise
• Jira
• CI/CD Platforms

Agile & Delivery Metrics

• Agile Methodologies
• Scrum
• Kanban
• Sprint Metrics
• Cycle Time
• Lead Time
• Throughput
• Deployment Frequency
• DORA Metrics

Reporting & Dashboards

• Dashboard Development
• Engineering KPIs
• Executive Reporting
• Data Visualization
• Analytics Frameworks

DevOps & Observability

• DevOps Practices
• Application Observability
• Software Delivery Lifecycle
• Release Management

Soft Skills

• Stakeholder Management
• Cross-functional Collaboration
• Problem Solving
• Communication
• Leadership

Required Qualifications

• Bachelors degree in Computer Science Information Technology Engineering or a related field.
• 6-8 years of experience in software engineering DevOps engineering operations or engineering analytics.
• Hands-on experience with Jellyfish or a similar engineering intelligence platform.
• Experience integrating Azure DevOps GitHub Enterprise and Jira.
• Strong understanding of Agile software delivery and SDLC.
• Experience building dashboards and analytics for engineering leadership.
• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Experience supporting AI/ML development lifecycle (AI DLC).
• Knowledge of observability platforms (Grafana Datadog Splunk New Relic Dynatrace etc.).
• Experience with DORA metrics and engineering productivity frameworks.
• Exposure to cloud platforms such as Azure or AWS.
• Experience working in enterprise digital transformation programs.