BI and Engineering Analyst

IRIS Software Group; England; On-site; GBP 85,000 - 110,000; Full time

Job summary

IRIS Software Group is seeking an analytical leader to transform engineering data into strategic dashboards and decision-ready insights. You will own end-to-end data and reporting for the Engineering Transformation Programme, connecting Jira, GitHub, Datadog and HR data to deliver trusted metrics for executives.

You will design scalable reporting frameworks, translate business questions into data outputs, and enable leaders to act on evidence-based insights across engineering productivity,

Qualifications

• Solid background in data analysis and BI in a software/tech organisation.

Responsibilities

• Collate and integrate data from multiple sources across the engineering estate — including Jira, GitHub/Azure DevOps, Datadog, Aha!, HR systems and programme-specific trackers.
• Design and own the metrics framework for the Engineering Transformation Programme, covering engineering productivity, quality, delivery and workforce transition.
• Build and maintain dashboards and reports for programme leadership, divisional VPs, the CTO and the CPO, ensuring they are accurate, timely, and fit for purpose.
• Translate stakeholder questions into data problems and data findings into accessible outputs.
• Establish repeatable, low-maintenance data pipelines where possible, reducing the reliance on manual collation and one-off analysis.
• Support the Central VP's and the Director of Agentic SDLC with data and reporting relevant to their workstreams.
• Flag data quality issues proactively and surface solutions where data is inconsistent or missing.
• Create executive-level dashboards that drive informed decision-making.
• Build consistent metrics and reporting standards across programme workstreams.
• Develop reporting frameworks that can scale with organisational maturity.
• Ensure stakeholders can trust the integrity and accuracy of the data they rely on.
• Identify trends, risks and opportunities within engineering and workforce data.

Skills

Data analysis

BI tooling

Power BI

Tableau

Looker

SQL

Python

Data pipelines

Tools

Jira

GitHub

Azure DevOps

Datadog

Pendo

Job description

Transform Engineering Data into Strategic Decisions

IRIS's Engineering teams generate a significant volume of data across multiple sources, from engineering metrics and tooling telemetry to workforce data, product telemetry and programme reporting.

Today, much of this data exists in separate systems, is manually consolidated when needed, and does not consistently feed into standardised dashboards that support decision-making across teams, divisions and the executive leadership team.

We're looking for a highly analytical and commercially minded leader to change that.

This role will establish the reporting, metrics and data foundations that enable the Engineering Transformation Programme to operate with a consistent, evidence-based view of progress. You'll connect disparate data sources, build trusted reporting frameworks, and deliver insights that genuinely help leaders make better decisions.

This isn't purely a Data Engineering role, and it isn't purely a Business Intelligence role. Success requires someone who can move seamlessly between the technical and the practical, understanding the underlying data while delivering outputs that are useful to the people making decisions.

The ideal candidate combines analytical rigour with pragmatism, understanding that a useful dashboard delivered today is often more valuable than a perfect dashboard delivered too late.

What You'll Be Doing

Engineering Data & Reporting Strategy

You'll own the end-to-end data and reporting capability supporting the Engineering Transformation Programme.

Key responsibilities include:

• Collate and integrate data from multiple sources across the engineering estate — including Jira, GitHub/Azure DevOps, Datadog, Aha!, HR systems and programme-specific trackers.
• Design and own the metrics framework for the Engineering Transformation Programme, covering engineering productivity, quality, delivery and workforce transition.
• Build and maintain dashboards and reports for programme leadership, divisional VPs, the CTO and the CPO, ensuring they are accurate, timely, and fit for purpose.
• Translate stakeholder questions into data problems and data findings into accessible outputs. Understand what a VP actually needs to see, not just what the data can produce.
• Establish repeatable, low-maintenance data pipelines where possible, reducing the reliance on manual collation and one-off analysis.
• Support the Central VP's and the Director of Agentic SDLC with data and reporting relevant to their workstreams.
• Flag data quality issues proactively. Where source data is inconsistent, missing, or unreliable, surface that clearly rather than papering over it, ideally with an accompanying solution.

You'll serve as the analytical backbone of the Engineering Transformation Programme, supporting leaders with accurate and actionable reporting.

You'll:

• Create executive-level dashboards that drive informed decision-making.
• Build consistent metrics and reporting standards across programme workstreams.
• Develop reporting frameworks that can scale with organisational maturity.
• Ensure stakeholders can trust the integrity and accuracy of the data they rely on.
• Identify trends, risks and opportunities within engineering and workforce data.

Future Growth Areas

• As the programme matures and the supporting data infrastructure evolves, the role is expected to expand into strategic areas including:
• Quality signals as a product input, helping close the loop between Datadog, Pendo and the PDLC so that quality data informs roadmap decisions.
• Self-service reporting capabilities for divisional engineering leaders.
• Contribution to the long-term data strategy for Engineering Operations as the function grows.

What We're Looking For

• Solid background in data analysis and BI, ideally in a software or technology organisation. Comfortable working with engineering, product and operational data.
• Hands-on experience building dashboards and reports in one or more mainstream BI tools — Power BI, Tableau, Looker, or equivalent. Not just maintaining existing dashboards, but designing them from scratch for a specific audience.
• Comfortable with SQL at a working level. Python or similar scripting capability is a plus, particularly for data wrangling and pipeline automation.

Leadership Style & Approach

We are looking for someone who:

• Is pragmatic first, perfect second. Delivers a useful dashboard quickly, then iterates, rather than spending weeks building the ideal solution that arrives too late.
• Asks the right questions before building. Understands that the stated request and the underlying need are not always the same thing.
• Is a clear communicator who can present findings to non-technical stakeholders without hiding behind data complexity.
• Is self-sufficient and organised, capable of managing multiple requests across different workstreams.
• Is comfortable with ambiguity in source data and surfaces data quality issues honestly rather than producing outputs that look clean but cannot be trusted.

Nice to Have

• Familiarity with engineering metrics frameworks such as DORA metrics, deployment frequency, lead time for change and change failure rate.
• Practical experience integrating data from multiple source systems using APIs, connectors or automated extraction methods.
• Experience working with engineering platforms such as Jira, GitHub, Azure DevOps, Datadog or similar tooling ecosystems.
• Exposure to engineering transformation, software delivery or operational excellence programmes.