Software Delivery Metrics Analyst (Power BI, DORA, GenAI)

Quick Facts

• Role: Software Delivery Metrics Analyst (Power BI, DORA, GenAI)

Description

You will analyze and design software delivery and DevOps metrics, integrate data across Jira, GitLab, GitHub, and Gerrit, and build KPI dashboards in Power BI. You will compute DORA metrics (deployment frequency, lead time for changes, change failure rate, failed deployment recovery time, rework rate) and translate results into business and operational recommendations. You will also assess GenAI tooling adoption and measure impact on productivity, quality, and ROI, with support for LLM-based integrations.

Responsibilities

• Evaluate current metrics and define new metrics aligned to organizational goals

• Implement end-to-end metrics: definitions, data sources, automation, and dashboarding

• Collect and join data from Jira, GitLab, GitHub, and Gerrit (via API and SQL)

• Calculate and monitor DORA metrics plus lead time, cycle time, and flow metrics

• Build and evolve Power BI KPI dashboards

• Interpret KPI results, identify bottlenecks, and explain findings to teams and management

• Map metric outcomes to business meaning (e.g., time-to-market, delay cost, client risk, rework cost)

• Measure GenAI adoption effects and productivity/quality/ROI impact

• Support solutions based on LLM/API integrations

• Document metric definitions, methodologies, and reporting in Confluence; prepare and present recommendations

Requirements

• 3-5+ years of experience in data analytics, Platform Engineering, DevOps, or Agile/IT process analytics

• Very good Jira skills (JQL, workflow, status history, dashboards)

• Very good Confluence skills

• Practical GitLab skills (CI/CD, pipelines, deployments, Merge Requests)

• Practical GitHub skills (repositories, Pull Requests, GitHub Actions, API)

• Practical Gerrit skills (code review workflow, patchsets, review times)

• Strong SQL skills (JOIN, aggregations, CTE, window functions)

• Practical Power BI skills (data modeling, Power Query, DAX, dashboards)

• Understand how LLMs work, including constraints (hallucinations, data security, costs)

• Practical prompt engineering and basic RAG knowledge

• Experience integrating LLMs into apps/processes via API

• Hands-on use of GitHub Copilot and knowledge of its adoption metrics

• Use of Microsoft Copilot in daily analytical work

Benefits

• Long-term cooperation

• Benefits package: Multisport, private medical care, life insurance

• Training budget

• Free English lessons

• Individual support from a dedicated company coordinator