Skills
• Financial Analytics: revenue forecasting, profitability modelling, variance analysis, budgeting support
• Risk & Customer Analytics: churn, LTV, segmentation, behavioural modelling
• Data Engineering: SQL Server, Azure SQL, SSIS, ADF, Fabric Lakehouse
• Modelling: Python (pandas, forecasting, churn, LTV), SQL window functions
• BI & Reporting: Power BI (DAX, semantic models, RLS), SSRS, SSAS
• Automation: Power Automate, VBA, reconciliation workflows, audit trails
• Data Integration: CRM, Finance, product, customer, operational datasets
• Governance: data quality, controls, documentation, RACI
MIS:
• ILR assurance, funding rule validation, planned and actual hours checks, prior attainment and EHC accuracy
• ProSolution, ProAchieve, ProMonitor and OneFile lifecycle mapping
• HE continuation, progression and completion metrics
• Attendance, retention, achievement and utilisation reporting
• Curriculum performance monitoring and quality improvement intelligence
• Apprenticeship compliance: off‑the‑job hours, gateway readiness, EPA tracking
• ELT reporting cycles: bi‑weekly, monthly, termly and annual
• Audit readiness, data quality controls and exception reporting
• Cross‑system integration of student records, HR contracts, timetables and finance data
About
Data Analytics Engineer with strong experience building multi domain data pipelines, modelling CRM, Finance, operational and customer datasets, and engineering reliable data flows across Finance, Commercial, Education and Healthcare environments. Skilled in designing schemas, developing ETL processes, implementing data quality frameworks and delivering automated reconciliation and validation workflows.
Expert in SQL, Python, SSIS, ADF, Fabric, Power BI and automation tools, with hands‑on experience integrating complex source systems, optimising data structures and supporting scalable reporting and analytics. Former Lecturer with strong communication skills and the ability to explain technical concepts clearly to non-technical stakeholders.
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