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IT Data Analysts

icon building Company : Sabenza It
icon briefcase Job Type : Full Time

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Job Description - IT Data Analysts

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


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