Data Analytics Manager

Lunio helps the world's leading advertisers protect and optimise their media spend, processing and analysing billions of ad interactions. The analytics function plays a critical role in this mission, transforming large-scale data into insights that drive decision-making for both our customers and internal teams.

The Data Analytics Manager will lead the analytics function, combining hands‑on analytical delivery with the coaching and development of a small team of analysts. A key focus of the role will be improving the efficiency and impact of the team through automation, AI-assisted workflows and better reporting, reducing avoidable reactive work and creating capacity for higher‑value analysis, while fostering a collaborative culture that supports growth, ownership and high‑quality delivery.

• Team Leadership & Development
  :
  Coach, and mentor a team of 2 data analysts, fostering a positive culture where people feel supported and motivated to grow.
• Data Service Delivery
  :
  Own the day‑to‑day operation of the analytics service, ensuring requests are effectively triaged, prioritised and delivered to a high standard. Maintain clear workflows and visibility through Jira, enabling effective planning and communication of progress.
• Hands‑On Analytics & Reporting
  :
  Contribute directly to analysis, reporting, dashboard development and experimentation, delivering high‑quality analytical outputs that support decision‑making across the business. Ensure dashboards and reporting solutions remain accurate, relevant and aligned to stakeholder needs.
• Stakeholder Partnership
  :
  Build strong relationships across the business, translating stakeholder needs into analytical solutions, managing expectations, and promoting data‑driven decision making.
• Automation & Continuous Improvement
  :
  Identify opportunities to automate repetitive analytical workflows and leverage AI‑assisted tooling to improve team efficiency, scalability and impact. Work closely with Data Science and Engineering teams to deliver larger automation and tooling initiatives where appropriate.

Strong SQL and Python skills with the ability to work independently on complex analytical problems and large datasets in cloud data warehouses (e.g. AWS Redshift, Databricks etc.)

Strong experience building and maintaining dashboards in BI tools such as Quick Sight, Looker, Tableau, or Power BI.

Solid understanding of statistical concepts (i.e. A/B testing, regression analysis, and experimental design).

Curious and pragmatic about AI‑assisted tooling, has practical experience embedding it to free up analyst time by automating repetitive workflows, not just experimenting.

Proven ability to manage competing priorities, triage requests, and communicate effectively with stakeholders across the business, and push back when needed. Comfortable operating ticketing systems such as Jira, managing expectations, and ensuring work is delivered consistently and at a high standard establishing clear SLAs

Able to turn data into compelling and actionable narratives. Thinks beyond the obvious metrics, identifies meaningful insights and alternative perspectives, and helps stakeholders understand what actions to take.

Takes ownership of problems from identification through to resolution. Comfortable making decisions independently, seeking guidance when appropriate, and ensuring work progresses reliably.

Able to structure ambiguous business questions, break down complex problems into manageable components, and apply sound analytical thinking to reach practical conclusions.

Builds trusted relationships across the business, communicates insights clearly, manages expectations effectively, and uses data to support decision‑making and drive action.

Actively seeks opportunities to improve or automate processes, develop new skills, and adopt better ways of working. Encourages learning, experimentation, and continuous improvement within the team.

In your first 6 to 12 months, we would expect to see:

• Strengthen the analytics…