WE ARE HIRING!

A leading organisation in the healthcare and manufacturing sector is looking to appoint a dynamic, passionate, confident, proactive, and meticulous
Data Analyst
to join a goal-oriented team.

The successful candidate will play a key role in transforming data into actionable business insights, developing scalable data solutions, and supporting data-driven decision-making across the organisation.

QUALIFICATIONS NEEDED

Required:

• 
  BSc / BCom in Computer Science, Statistics, Data Science, Mathematics, or related field

Preferred:

• 
  Honours or postgraduate degree in Data Science or Applied Mathematics
• 
  Experience in pharmaceutical, life sciences, or regulated manufacturing environments (GxP advantage)
• 
  Prior pharmaceutical or regulated manufacturing experience is advantageous

EXPERIENCE REQUIRED

• 
  Proven delivery of end-to-end data projects from raw data through to business output
• 
  Strong proficiency in Python for data manipulation, modelling, and automation
• 
  Hands-on experience with Microsoft Fabric (Lakehouses, Pipelines, Notebooks, Semantic Models)
• 
  Power BI dashboard and report development including DAX and data modelling
• 
  SQL and relational/non-relational database expertise
• 
  Data engineering fundamentals including ETL/ELT processes
• 
  Experience with data visualisation, reporting, and storytelling
• 
  Knowledge of cloud-based data architecture and platforms

Preferred Experience:

• 
  Exposure to Azure Data Services (Synapse, Data Factory, ADLS)
• 
  Experience with MLOps and model deployment
• 
  Familiarity with GMP/GxP data integrity requirements

Requirements

KEY DUTIES & RESPONSIBILITIES

Core Technical Delivery

Data Engineering & Pipeline Management

• 
  Design, build, and maintain scalable ETL/ELT pipelines within Microsoft Fabric
• 
  Ingest, cleanse, and transform structured and unstructured datasets
• 
  Manage Lakehouse architecture, data flows, and Fabric workspaces
• 
  Monitor pipeline performance and implement data quality controls
• 
  Ensure data lineage, cataloguing, and governance compliance

Analytics, Modelling & Insights

• 
  Develop statistical and machine learning models to solve business challenges
• 
  Conduct exploratory data analysis and communicate findings to non-technical stakeholders
• 
  Build and maintain Power BI dashboards and semantic models
• 
  Translate business requirements into data hypotheses and actionable insights
• 
  Conduct forecasting and trend analysis where required

Quality & Data Governance

• 
  Ensure all data processes comply with organisational governance and quality standards
• 
  Maintain audit-ready documentation of data models, pipelines, and outputs
• 
  Support the development of a strong data quality culture across the organisation
• 
  Identify and remediate data integrity risks proactively

Collaboration & Stakeholder Engagement

• 
  Collaborate with business units and leadership teams to prioritise data requirements
• 
  Present findings, reports, and dashboards to management and executive stakeholders
• 
  Mentor junior analysts where applicable
• 
  Work closely with IT teams regarding infrastructure and data security requirements

TECHNICAL COMPETENCIES

• 
  Ability to communicate technical concepts to non-technical audiences
• 
  Statistical modelling and machine learning using libraries such as scikit-learn and statsmodels
• 
  Power BI expertise including DAX, Power Query, and Semantic Model design
• 
  Data visualisation best practices
• 
  Experience with Notebooks, VS Code, and Fabric Notebooks
• 
  Microsoft Fabric (Pipelines, Dataflows, Lakehouses, Notebooks)
• 
  Python (pandas, PySpark, NumPy)
• 
  SQL / T-SQL / KQL
• 
  Azure Data Lake Storage and cloud data infrastructure
• 
  ETL design patterns and orchestration
• 
  Data governance frameworks and metadata management
• 
  Enterprise data platforms including Microsoft Fabric, Azure, and Power BI
• 
  Data engineering and integration methodologies
• 
  Data storytelling and business insight generation
• 
  Cloud-based data architecture principles