Senior Analyst

As a Senior Analyst, you will build, support, and optimise modern data solutions and analytical products across the Azure Data Platform. You'll design and manage robust data pipelines (Azure Data Factory, Databricks, Data Lake, and Synapse); lead the development of Power BI dashboards and semantic models (including Power BI Server); and perform advanced Excel-based analysis for rapid insights. You will collaborate closely with business stakeholders, data engineers, and data scientists to deliver reliable, secure, and scalable data products that drive decision-making, particularly within supply chain and CPG contexts. Note: This role includes production support, monitoring, and potential rotational shift coverage (including night shifts if required).

Responsibilities:

Data Engineering and Platform Operations.

BI Development and Data Visualisation.

Excel-Based Data Analysis.

Stakeholder Engagement and Domain.

Design, develop, customise, and manage data integration tools, data lakes, warehouses, and analytical systems on Azure.

Build, scale, and harden data pipelines (internal and external sources) using Azure Data Factory, Azure Databricks (PySpark/Spark SQL), Azure Data Lake, Azure Synapse, and Azure SQL.

Own automation, observability, and monitoring frameworks capturing operational KPIs and data quality metrics; set up alerting and runbooks.

Deploy pipelines to production, manage compute resources, configure data attributes, set up monitoring tools, and ensure resilient operations.

Monitor performance and stability, triage incidents, and adapt pipelines as data/models/requirements evolve.

Implement best practices for systems integration; security (RBAC, Key Vault, RLS/OLS); performance; cost optimisation; and data governance.

Apply DevOps/DataOps/Agile methodologies; manage version control (Git/Bitbucket) and CI/CD pipelines (Azure DevOps/Jenkins) for data and BI assets.

Conduct data validation and unit/integration testing and partner with test teams for end-to-end assurance.

Lead the development of advanced Power BI reports/dashboards and semantic models (star schema and tabular modelling); optimise Power BI Server for scale and performance.

Write advanced DAX measures and Power Query (M) transformations and design model relationships to deliver trustworthy, performant analytics.

Establish BI governance (naming standards, measure tables, calculation groups, RLS, deployment pipelines, workspace and gateway management).

Collaborate with cross-functional teams to integrate Power BI with other digital solutions and drive analytics innovation; mentor junior BI developers.

Maintain and continuously improve existing BI solutions in line with evolving business needs.

Perform advanced Excel analysis (PivotTables, Power Pivot, Power Query, XLOOKUP/INDEX-MATCH, array formulas, and scenario analysis); create executive-ready summaries.

Build ad-hoc analytical models and data checks that complement pipeline outputs and BI dashboards.

Partner with business, IT, and SMEs to translate requirements into scalable data products; lead solutioning and POC discussions.

Requirements:

Demonstrate strong storytelling by turning complex datasets into compelling, actionable insights for non-technical stakeholders.

Preferred: Experience in CPG supply chain (planning, sourcing, manufacturing, logistics, and customer service) and related KPIs.

Bachelor's degree in engineering, computer science, data analytics, IT, or a related field.

4-6 years of relevant experience across Azure Data Engineering and Power BI.

Hands-on expertise with Azure Databricks (PySpark/Spark SQL), Azure Data Factory, Azure Data Lake, Azure Synapse, Azure SQL, Power BI/Power BI Server (DAX, data modelling, Power Query M, RLS, performance optimisation), and SQL/T-SQL (complex queries, stored procedures).

Desired Qualifications:

Experience with Git/Bitbucket, Azure DevOps/Jenkins for CI/CD of data and BI assets.

Strong scripting, data modelling, and programming fundamentals.

Solid understanding of cloud architecture principles (security, scalability, reliability, cost).

Excellent communication, stakeholder management, and the ability to mentor others.

Shift flexibility, including night shifts if required.