Data Analytics & Insight Manager

Role Purpose Support data insights, dashboards, business intelligence (BI), omnichannel analytics, and practical data solutions to enable operational, HCP engagement, stakeholder, and organisational performance visibility and data-informed decision-making across relevant operations. This is an individual-contributor manager role with no direct or indirect reports, contributing through hands-on analytical expertise, cross-functional collaboration, and delivery of BI, data analytics and insights. Key Responsibilities Generate insights across omnichannel activities, HCP engagement, event execution and operational performance by integrating HCP journey data, behaviour patterns, content interaction, channel effectiveness and relevant operational context to identify opportunities and support data-informed decision-making. Provide relevant analytics, dashboards, insights and practical decision support that help stakeholders prioritise actions, improve operational effectiveness and strengthen KPI visibility. Generate operational performance insights, track KPIs, visualise trends in Power BI and communicate clear data stories that support operational planning, reporting and decision making. Support operational processes and event management through analytics, data tracking, reporting and monitoring of execution against compliance requirements. Ensure appropriate handling, access, sharing and use of data, reports and insights in line with company policies, data governance requirements, privacy standards and applicable regulations. Perform hands-on data analytics and end-to-end data processing across digital platforms and operational systems, including extraction, cleansing, transformation, validation, mapping, reconciliation and consolidation across multiple sources. Handle ad-hoc, semi-structured and unstructured data to build reliable analysis-ready datasets, define metrics and tracking logic, and support omnichannel execution, event follow-up, HCP engagement analysis and operational performance monitoring. Support data engineering activities by contributing to the design, implementation, optimisation and maintenance of data pipelines, ETL/ELT workflows, scalable data applications, data tables and automated jobs in Azure Databricks using SQL and Python, under agreed architecture and governance standards. Contribute to BI development and dashboard design in Power BI, including semantic modelling, KPI logic, visual design, usability, storytelling, performance improvement and reusable data assets across analytical workflows. Support cross-functional analytics and BI projects from requirements gathering through delivery by working with operational and technical stakeholders on priorities, scope, quality, timelines, expected outcomes, automation opportunities and AI-enabled productivity improvements where appropriate. What we are looking for? Education Bachelor’s degree in Computer Science, Data Analytics, Data Science, Information Systems or other related disciplines. This level of education is required to provide a solid foundation in data, analytics and information systems for hands-on analysis, BI development, data engineering and practical solution design. Preferred MSc in Computer Science, Data Analytics, Data Science or related disciplines. An advanced degree is preferred as it strengthens analytical thinking, technical problem-solving and the ability to support data and BI solution design in operational environments. Other job-related experience 5&#43; years of relevant experience in BI, data analytics, omnichannel analytics or operational performance analytics. Hands-on experience in data processing, insight generation, dashboard development and data solution delivery. Strong experience with SQL and Power BI, and working with both structured and unstructured data. Exposure to or experience with Python, Azure Databricks, ETL/ELT workflow design and data engineering is preferred. This level of experience is required to provide a balanced mix of hands-on analytics, insight generation, BI development, practical data engineering exposure and cross-functional collaboration, enabling reliable BI, data solutions and effective decision support across relevant operations. Skills & Knowledge Operational & analytics skills Hands-on data analytics and data processing Insight generation and operational analytics Performance analysis and KPI tracking Data visualisation and storytelling with Power BI Ad-hoc analytics and unstructured data analysis Omnichannel analytics and strong understanding of operational performance Technical skills Data pipeline development, ETL/ELT and scalable data solutions Data management, data quality and data governance Azure Databricks data tables, workflows and job management SQL and Python for data engineering and analytics BI development, semantic modelling and dashboard design in Power BI Database structure, schema design and performance improvement Automation and AI-enabled productivity improvement Behavioural skills Stakeholder collaboration and cross-functional teamwork Strong ownership of assigned deliverables Problem-solving mindset and solution orientation Effective communication with technical and non-technical stakeholders Tools knowledge Power BI SQL Python Azure Databricks MS Office Suite *Li-GSK <br