Data Analytics and Insights Manager

Interactive Investor; Leeds; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Group Personal Pension Plan

Life Assurance

Private Medical Insurance

25 Days Annual Leave

Staff Discounts

Well-being Fund

Retail Discounts

Voluntary Flexible Benefits

Job summary

Interactive Investor is seeking a Data Analytics and Insights Manager to lead the analytics centre of excellence, shaping what to measure, building an prioritised analytics roadmap, and ensuring trusted data for decision-makers across the business. You’ll drive self-service adoption and maintain data quality and semantic consistency.

You will mentor a team of Data Analysts, collaborate with Data Engineering, Data Science, and business units, and champion AI-enabled analytics to accelerate

Qualifications

• Experience with modern BI and reporting tools (e.g. Power BI).
• Proven ability to lead analytics strategy, roadmaps and governance.
• Strong data modelling, metrics governance, and semantic layer experience.
• Experience building data products and self-service analytics.

Responsibilities

• Define analytics-as-a-service strategy and prioritised briefs.
• Own analytics roadmap and governance across data platform and teams.
• Lead, mentor, and grow a team of Data Analysts.
• Deliver analytics that drive commercial performance, product improvement and customer experience.
• Ensure data quality, discoverability, and metadata standards across the estate.
• Partner with cross-functional teams to deliver AI-enabled self-service analytics.

Skills

Advanced SQL

Data modelling

Data visualization

Applied statistics

Power BI

Streamlit

Stakeholder management

People leadership

Tools

Dagster

CI/CD

Snowflake

BigQuery

Job description

As Data Analytics and Insights Manager at interactive investor, you lead our Data Analytics and Insights team and own analysis, reporting, and analytics strategy across the business. You run our centralised centre of excellence for business intelligence, management information, and insight. Your team's work reaches colleagues and decision-makers right across interactive investor. You'll define what the business needs to measure and why, translate that into a prioritised analytics roadmap, and make sure the answers people get are accurate, timely, and genuinely useful. Just as importantly, you'll build the conditions for self-service, so that routine questions can be answered by the people asking them and your team's time goes to the questions that need real thought. You'll set the standards for how analytics is built here: governed metric definitions and a shared semantic layer so numbers agree across the business, a well-maintained data catalog and ontology so data assets are discoverable and trusted, version control, testing, and documentation as normal practice, and AI used as a core, everyday part of the team's workflow, not an optional extra, speeding up everything from exploration to narrative reporting. Working on a "you build it, you run it" basis, your team looks after what it produces - dashboards and reporting products are kept accurate, refreshed as the business changes, and retired when they've served their purpose, so the estate stays trustworthy rather than sprawling. You'll partner closely with peers across the division. The Data Engineering and Platform Manager owns the platform, pipelines, and analytics instrumentation your team depends on; you own what the business needs from it, though in practice the line is deliberately soft, and you'll shape feasibility together from the start. The Data Science and Enterprise AI Manager owns predictive modelling and Enterprise Agents and AI; you'll work together to spot where a model, rather than a report, is the better answer. Beyond the division, you'll partner with teams like Commercial, Product, Marketing, Customer Services, Operations, Compliance, and Legal. As a manager, you'll lead, mentor, and grow a team of Data Analysts, balancing hands-on analysis with strategy and leadership. It's a role that rewards pace and accuracy in equal measure, in a team where people pair on problems rather than pass them over a wall., Strategy and technical leadership

Strategy and technical leadership

• Define the analytics-as-a-service strategy: what the business needs to measure, why it matters, and how insight reaches decisions
• Engage stakeholders to understand their questions, translating business need into clear, prioritised analytics briefs
• Own the analytics roadmap across people, process, and priority, shaped jointly with the Data Engineering and Platform Manager where platform capability is involved
• Treat AI as an essential, everyday tool across the team's analytics workflows, and continually adopt the capabilities that genuinely speed up or improve the work
• Work hand-in-hand with the Data Engineering and Platform team (platform, pipelines, instrumentation) and the Data Science and Enterprise AI team (predictive modelling, Enterprise Agents, AI-enabled self-service) to shape feasibility jointly and deliver joined-up outcomes across the Data and Enterprise AI division

Serving the business

• Understand where teams across the business get most value from data, and shape the team's priorities around them
• Balance and prioritise competing demands transparently, so stakeholders understand what they're getting and when
• Drive genuine adoption - insight that reaches real decisions rather than stopping at a dashboard
• Grow self-service, so colleagues can answer routine questions confidently and safely for themselves
• Partner with the Data Science and Enterprise AI team to deliver AI-enabled self-service analytics, grounded in governed semantic views, so colleagues can query trusted data directly in natural language rather than waiting on bespoke reporting

Insight and delivery

• Build and maintain lightweight data products (e.g. Streamlit apps) for data consumers, as an alternative to traditional BI dashboards where that's the better way to put insight directly in people's hands
• Deliver analysis and management information that drives commercial performance, product improvement, better customer experiences, and operational efficiency
• Agree and monitor the KPIs the business runs on, and report clearly on what they're telling us
• Bring insight into customer behaviour, needs, and journeys to support personalisation, targeting, and product decisions
• Support experimentation and A/B testing, so changes are measured properly rather than assumed to have worked

Standards and quality

• Own governed metric definitions, a shared semantic layer, the data catalog, and the wider data ontology, ensuring the same question gets the same answer wherever it's asked, data assets are findable and trusted, and metadata, lineage, and business definitions stay accurate as the data estate evolves
• Set standards for analytics engineering: modelling, version control, testing, documentation, and peer review
• Monitor and continuously improve data quality with analysts, engineers, and subject matter experts, and be clear about limitations where they exist
• Keep the reporting estate healthy - refreshed, understood, and retired when no longer needed

Governance and compliance

• Define analytics requirements for data governance and privacy, particularly around web and mobile analytics data
• Work with Compliance, Information Security, Legal, and Data Engineering and Platform to ensure practice meets the Cookies Policy, GDPR, and other applicable obligations
• Apply Enterprise AI Centre of Excellence standards where AI-assisted analytics is used, keeping outputs reviewable and appropriately controlled
• Participate in risk management and root cause analysis, promoting continuous improvement

People and delivery

• Lead, mentor, and develop a team of Data Analysts, managing workload against strategic priority
• Support hiring, onboarding, and capability development as the team matures
• Communicate clearly with senior stakeholders, and report honestly on impact, progress, and trade-offs
• Facilitate knowledge sharing and act as an advocate for good analytics practice across the business
• Strong hands-on analytical capability: advanced SQL, data modelling, visualisation, and applied statistics
• Experience with modern BI and reporting tools, such as Power BI, and lightweight app frameworks such as Streamlit, with a track record of building data products people actually use
• Experience defining and governing metrics, ideally including semantic layer or single-source-of-truth approaches
• Solid understanding of digital analytics platforms, such as Google Analytics and Matomo, and of journeys, cookies, and tracking methods - enough to define what's needed, with implementation owned by Data Engineering and Platform
• Hands-on experience embedding AI as a core, everyday tool in analytics workflows (e.g. AI coding assistants, LLM-based analysis agents), with a clear-eyed view of where it adds most value
• Experience enabling AI-driven self-service analytics (e.g. natural-language querying grounded in governed semantic views), ideally in partnership with data science or AI teams
• Experience owning or maintaining a data catalog, metadata, and ontology/taxonomy, alongside metric governance

Leadership and delivery

• Proven experience managing and mentoring a team of data professionals
• Ability to translate business strategy into an analytics roadmap and prioritise transparently across competing demands
• Excellent stakeholder management and communication skills across technical and non-technical audiences

Governance and domain

• Working knowledge of data governance and privacy obligations, including GDPR

Experience ensuring analytics outputs are accurate, documented, and appropriately controlled

Valuable Extras

• Analytics engineering practice: Dagster, version control, CI/CD, and automated testing
• Experience with cloud data platforms, such as Snowflake or BigQuery

• Group Personal Pension Plan - 8% employer contribution and 4% employee contribution
• Life Assurance and Group Income Protection
• Private Medical Insurance - Provided by Bupa
• 25 Days Annual Leave, plus bank holidays
• Staff Discounts on our investment products
• Personal & Well-being Fund - Supporting your physical and mental wellness
• Retail Discounts - Savings at a wide range of high street and online retailers
• Voluntary Flexible Benefits - Tailor your benefits to suit your lifestyle