Role overview
The Principal Data Analyst will lead significant areas of data analysis across AWTG and client programmes. The role sets standards for data analysis, governance, data quality and visualisation, while influencing strategic decisions through trusted evidence and insight. You will work with multidisciplinary teams across data, AI, software engineering, product, QA and delivery to create practical outcomes for clients and end users.
Key responsibilities
- Lead data analysis across major products, programmes or client portfolios, ensuring work aligns with organisational priorities.
- Set standards for analytical methods, data quality, documentation, reproducibility and quality assurance.
- Oversee the design and delivery of scalable data products, dashboards, reports and insight packs.
- Influence senior stakeholders by translating data into strategic recommendations and business impact.
- Champion data management, data governance, privacy and ethical use of data across teams.
- Mentor analysts and develop capability, standards and good practice within the data community.
Essential skills and experience
- Extensive experience leading data analysis in complex digital, operational or transformation environments.
- Expert understanding of statistical and analytical techniques, data management and visualisation standards.
- Ability to oversee the quality assurance of analytical outputs across teams and projects.
- Strong stakeholder management and communication skills at senior and executive levels.
- Experience defining data models, quality standards and reusable analytical approaches.
- Ability to lead, mentor and grow data analysis capability across a multidisciplinary organisation.
Desirable skills and experience
- Experience with BI platforms, SQL, Python/R, cloud data platforms and modern analytics engineering practices.
- Experience contributing to data strategy, data governance frameworks or enterprise reporting standards.
- Experience in consulting, public‑sector, regulated or client‑facing delivery.
What success looks like
- Data analysis standards are clear, adopted and continuously improved.
- Senior decisions are informed by reliable, well‑governed data and insight.
- Teams deliver scalable data products that create measurable business value.
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