Contract Description
Data Analyst (AI-Enabled Data Insights)
Company: Major UK broadcaster and media group, Group Technology function
Team: Data Insights
Travel: 2 days per week on site
Contract: Outside IR35
The company is running a large readiness programme to prepare its IT service management, asset/configuration, software-licensing and cloud-financial (FinOps) tooling for an organisational separation. By a defined "Day 1", data, access and reporting must be correctly segregated between parts of the business, with controls in place and evidence that the separation works. The Data Insights workstream owns the data and reporting side, and AI and automation are used across the pipeline from data prep to visualisation.
Bring AI capability into a small data team. This is a deliberate role for someone who has already built AI-driven data pipelines and visualisations and can teach the rest of the team to do the same. The work is turning data from many sources into clear dashboards and reports faster, to support better decisions.
Key responsibilities
What sets the ideal candidate apart is real, demonstrable AI use in the pipeline: LLMs for data cleaning, automated analysis, or AI-assisted dashboard building. Examples you can talk through matter more than buzzwords. They also need to be a good communicator and mentor, since part of the job is upskilling the team.
Useful background would be FinOps or cloud cost work, ITSM data (ServiceNow, FreshService or similar), and any experience with data segregation, RBAC or compliance reporting. Automation tools like n8n or SnapLogic are a bonus.
Company: Major UK broadcaster and media group, Group Technology function
Team: Data Insights
Travel: 2 days per week on site
Contract: Outside IR35
The company is running a large readiness programme to prepare its IT service management, asset/configuration, software-licensing and cloud-financial (FinOps) tooling for an organisational separation. By a defined "Day 1", data, access and reporting must be correctly segregated between parts of the business, with controls in place and evidence that the separation works. The Data Insights workstream owns the data and reporting side, and AI and automation are used across the pipeline from data prep to visualisation.
Bring AI capability into a small data team. This is a deliberate role for someone who has already built AI-driven data pipelines and visualisations and can teach the rest of the team to do the same. The work is turning data from many sources into clear dashboards and reports faster, to support better decisions.
Key responsibilities
- Deliver FinOps and data-separation requirements across multiple systems, making sure cloud account ownership is correctly reflected
- Build and maintain dashboards and reports (Looker Studio, Tableau or similar) that evidence data separation and support project delivery
- Analyse data from multiple sources (CMDB, software asset management, FinOps, identity, Jira, Slack, BigQuery, Matillion, SnapLogic, n8n, OpenAI) to surface trends, ticket volumes and insights
- Apply the authoritative "Org" identifier across reporting and help validate that role-based access controls (RBAC) work as intended
- Apply AI and automation from data preparation and cleansing through to analysis and visualisation, to cut manual steps and reduce data errors or unnecessary data visibility
- Capture requirements from technical and non-technical stakeholders and produce separation-evidence reporting for regulatory obligations
- Build measurement into deliverables and find improvements in service management reporting and FinOps visibility
- Hands-on experience building data pipelines and data products that use AI (cleaning data, speeding up analysis, producing insight)
- Experience using AI in data visualisation and reporting
- Strong SQL and Python (or similar), with BigQuery and Matillion experience
- Strong Looker Studio, Tableau or similar
- Track record of solving business problems through automation, increasingly AI
- Experience with a range of stakeholders, and able to explain insights plainly, including what AI can and can't do
- Agile working, adaptable to changing priorities
- Willing to teach, pair with colleagues and share what they learn
What sets the ideal candidate apart is real, demonstrable AI use in the pipeline: LLMs for data cleaning, automated analysis, or AI-assisted dashboard building. Examples you can talk through matter more than buzzwords. They also need to be a good communicator and mentor, since part of the job is upskilling the team.
Useful background would be FinOps or cloud cost work, ITSM data (ServiceNow, FreshService or similar), and any experience with data segregation, RBAC or compliance reporting. Automation tools like n8n or SnapLogic are a bonus.
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