Senior Data Analyst in London

Location: Remote or Hybrid (split between site-based and home-working)

Country: Flexible (UK/EU/US/Hong Kong)

Reports to: Global Head of Service Delivery, IT & Repairs

Contract Type: Permanent / Full-time

Contracted Hours/Days: 37.5 hours / 5 days per week

About Us: At Reveal, passion meets purpose. Our body-worn video solutions are more than just technology; they are a testament to our commitment to safety, innovation and change. Rooted in the UK, we have become a trusted ally for many police forces, local authorities, retailers and private organisations; helping to pioneer and drive the application of body-worn video in settings and geographies where we can see exciting potential. With an influence now spanning over 40 countries, our mission to make a positive impact continues to gain momentum.

Purpose of the Role: The Senior Data Analyst will play a critical role in enabling data-driven decision-making across Reveal’s global service organisation. This role is responsible for extracting, transforming, analysing, and visualising data from multiple enterprise systems—including Azure, Salesforce, Halo ITSM, and repair/logistics platforms—to deliver high-quality insights for senior executives, sales teams, service delivery, engineering, product teams, and customers. The role will design and maintain advanced Power BI dashboards, build robust data models, perform historical trend analysis, and develop forecasting and pattern-detection models to support operational planning and continuous improvement. In addition, this role will contribute to the evolution of AI-enabled analytics, using Python and modern AI tools (e.g. Copilot and ChatGPT-style agents) to enhance insight generation, automate analysis, and enable self-service reporting capabilities across the business. This role is critical to Reveal’s ability to scale service operations globally while maintaining service excellence, customer trust, and commercial performance. By combining advanced analytics, automation, and emerging AI capabilities, the Senior Data Analyst will help transform data into a strategic asset across the organisation.

Key Responsibilities:

• Data Extraction & Integration

• Design, build, and maintain reliable data pipelines to extract data from Azure, Salesforce, Halo ITSM, and other internal or third-party systems.
• Develop automated ETL processes to ensure timely, accurate, and scalable data refresh cycles.
• Work with development teams and system owners to integrate data via APIs and improve data availability.
• Build and maintain robust data models to support operational, commercial, and executive reporting.
• Analyse service delivery performance including SLAs, KPIs, MTTR, incident volumes, backlog trends, repair cycle times, and device failure patterns.
• Perform historical trend analysis and develop forecasting models to support capacity planning, staffing decisions, and risk identification.
• Identify patterns, anomalies, and systemic issues that impact service quality or cost-to-serve.
• Design and deliver high-quality Power BI dashboards tailored to different audiences, including senior executives, sales teams, service operations, and customers.
• Standardise KPI definitions and reporting structures across regions (UK, Germany, US, Hong Kong).
• Automate recurring reports and reduce reliance on manual, spreadsheet-based reporting.
• Ensure dashboards tell a clear, actionable story rather than simply presenting data.

• Use Python to automate data processing, analysis, and reporting workflows.
• Contribute to the design and development of AI-assisted analytics solutions, including Copilot-style or ChatGPT-based agents to support insight generation, reporting, or operational queries.
• Natural-language interfaces for exploring service data.
• Partner with stakeholders to identify high-value use cases where AI can enhance decision-making or operational efficiency.
• Provide analytical insight to support continuous improvement initiatives across service delivery and support operations.
• Support monthly and quarterly service reviews with strategic customers through high-quality analytics packs and performance narratives.
• Enable proactive decision-making by identifying emerging risks before they impact customers or SLAs.

• Establish and maintain data governance standards, KPI definitions, and documentation.
• Ensure data accuracy, integrity, and consistency across all reporting outputs.
• Identify data quality issues and work with system owners to drive upstream improvements.

• Work closely with Service Delivery, Engineering, Product, Sales, Finance, and Customer Success teams.
• Act as a trusted analytics partner to senior leadership, translating complex datasets into clear, concise insights.
• Present findings confidently to executive stakeholders and external customers.

Learning and Development: We encourage continuous professional development and support learning through on-the-job experience, feedback and access to relevant training opportunities. You are expected to take ownership of your development and maintain up-to-date knowledge of sector trends, technology and best practice relevant to your role.

Qualifications, Skills and Experience:

• 5–7+ years’ experience as a Senior Data Analyst, BI Analyst, or Analytics Specialist, ideally within SaaS, ITSM, or service-led organisations.
• Strong Python experience (essential), including use for data analysis, automation, modelling, and system integration.
• Advanced SQL skills and experience building and maintaining ETL pipelines.
• Advanced Power BI expertise, including DAX, dataflows, model optimisation, and performance tuning.
• Proven experience extracting and working with data from Azure, Salesforce, and ITSM platforms (Halo ITSM preferred).
• Strong understanding of service delivery and operational metrics (SLAs, KPIs, MTTR, backlog management, incident trends, repair logistics).
• Demonstrated experience with forecasting, time-series analysis, and pattern recognition.
• Ability to translate complex data into executive-level insights and compelling narratives.
• Strong communication and stakeholder management skills.
• Experience developing AI-assisted analytics solutions, including building Copilot, ChatGPT, or similar AI agents to support reporting, insight generation, or operational decision-making.
• Leveraging large language models (LLMs) to enhance data exploration or automation.
• Experience integrating Python analytics with Azure AI services (e.g. Azure OpenAI).
• Familiarity with modern data platforms (Azure Data Lake, Synapse, Snowflake, lakehouse architectures).
• Experience with predictive or prescriptive analytics beyond basic forecasting.
• Exposure to automation or orchestration tools for analytics pipelines.

Key Performance Indicators (KPIs):

• Accuracy, reliability, and consistency of reporting and data models.
• Adoption and usage of dashboards by executives and operational teams.
• Reduction in manual reporting effort across the business.
• Accuracy and usefulness of forecasting models.
• Measurable improvements in service performance visibility and decision-making speed.
• Data quality improvements across core systems.