Data Analyst

Biovac was founded in 2003 to revive and restore South Africa’s vaccine manufacturing capabilities. We are an African based manufacturer contributing towards filling the gap that exists in the lack of African vaccine manufacturing capability.

Job Purpose

To design, develop and maintain advanced data solutions that drive business intelligence and operational decision-making. The role will lead the full data lifecycle from ingestion and transformation through to modelling, visualisation and reporting, leveraging Microsoft Fabric, Python and Power BI to deliver actionable insights.

Requirements

Required:

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

• 3+ years hands-on experience in a data science or data engineering role

Preferred:

• Honours or postgraduate degree in Data Science or Applied Mathematics

• Experience in pharmaceutical, life sciences or regulated manufacturing (GxP advantage)

• Prior pharmaceutical or regulated manufacturing experience is advantageous.

Experience & industry knowledge

Required:

• Demonstrated delivery of end-to-end data projects from raw data to business output

• Proficiency in Python for data manipulation, modelling and automation

• Hands-on experience with Microsoft Fabric (Lakehouses, Pipelines, Notebooks, Semantic Models)

• Power BI report and dashboard development including DAX and data modelling

• TL/ELT pipeline design and management

• SQL and relational/non-relational database knowledge

Preferred:

• Exposure to Azure Data Services (Synapse, Data Factory, ADLS)

• Experience with MLOps and model deployment

• Familiarity with GMP/GxP data integrity requirements

Responsibilities

Data Engineering & Pipeline Management

• Design, build and maintain scalable ETL/ELT pipelines within Microsoft Fabric

• Ingest, cleanse and transform structured and unstructured data sources

• Manage Lakehouse architecture, data flows and Fabric workspaces

• Monitor pipeline performance and implement data quality controls

• Ensure data lineage, cataloguing and governance compliance

Technical Competencies:

• 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

Analytics, Modelling & Insights

• Develop statistical and machine learning models to solve business problems

• Perform exploratory data analysis and communicate findings to non-technical stakeholders

• Build and maintain Power BI dashboards and semantic models

• Translate business questions into data hypotheses and actionable insights

• Conduct forecasting and trend analysis as required

Technical Competencies:

• Statistical modelling and machine learning (scikit-learn, statsmodels)

• Power BI - DAX, Power Query, Semantic Model design

• Data visualisation best practices

• Notebooks / VS Code / Fabric Notebooks

Quality & Data Governance

• Ensure data processes adhere to organisational data governance and quality standards

• Maintain audit-ready documentation of data models, pipelines and outputs

• Participate in building a data quality culture across the business

• Proactively identify and remediate data integrity risks

Technical Competencies:

• Data governance frameworks and metadata management

• Documentation and version control (Git)

• Understanding of GMP/GxP data integrity requirements (advantageous)

Collaboration & Stakeholder Engagement

• Work closely with the Innovation Manager and business units to prioritise data needs

• Present findings and dashboards to management and executive teams

• Mentor junior analysts where applicable

• Engage with IT on data infrastructure and security requirements

Technical Competencies:

• Communication of technical concepts to non-technical audiences

• Stakeholder management and requirements gathering

• Agile / project-based ways of working

Closing date: 18 September 2026

If you do not receive a response from us within three weeks after closing date, please understand that your application was not successful.

We believe in the magic of diversity within teams and to achieve this, we do apply Employment Equity principles during our selection process where this is necessary to achieve such diversity.

Disclaimer:

Dear Applicant, we appreciate your interest in joining our organization. It is imperative for us that you understand how we handle your information. We are committed to ensuring the security and confidentiality of the information you provide. Your personal details will be collected for the sole purpose of the application process and will be used strictly for that purpose. By applying, you acknowledge and consent to the collection, use, and protection of your personal information in accordance with our privacy policy. If you have any inquiries or concerns, our Human Capital department is available to provide clarification. We look forward to reviewing your application