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Analytics Engineer (Business Intelligence and Reporting) - Hybrid

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Summary

Analytics Engineer joining a client's Data & Analytics team in Pretoria (hybrid), building trusted datasets, semantic models, and Power BI dashboards for business reporting. Day to day involves BI development, PySpark notebooks in Microsoft Fabric, and advanced SQL across the Microsoft Data Platform (Fabric, Synapse, Data Factory).

Our client is searching for an Analytics Engineer to join their Data & Analytics team in Pretoria (Hybrid).

This role is ideal for someone passionate about transforming data into meaningful business insights through Business Intelligence, reporting, and analytics.

The successful candidate will play a key role in developing trusted datasets, semantic models, dashboards, and analytical solutions that support data-driven decision-making across the organisation.

Working primarily with the Microsoft Data Platform, including Microsoft Fabric, Power BI, Azure Synapse Analytics, and Azure Data Factory, you will collaborate with business stakeholders to understand requirements and deliver scalable reporting and analytics solutions.

This role is suited to someone who enjoys solving business problems using data and wants to grow their skills in modern analytics technologies.

Key Responsibilities:

Business Intelligence & Reporting

  • Design, develop, and maintain Power BI dashboards, reports, scorecards, and visualisations.

  • Develop semantic models and reporting datasets that enable trusted self-service analytics.

  • Build dashboards and KPI reporting solutions for business stakeholders.

  • Develop and maintain Power BI Paginated Reports where required.

  • Assist with optimisation of Power BI models, DAX calculations, and report performance.

Analytics & Business Insights

  • Analyse datasets to identify trends, opportunities, risks, and business insights.

  • Work with business stakeholders to translate requirements into analytical solutions.

  • Define and maintain business KPIs and performance metrics.

  • Perform trend analysis and support business investigations through data analysis.

  • Present findings clearly to both technical and non-technical stakeholders.

Data Engineering & Data Preparation

  • Develop and maintain PySpark notebooks within Microsoft Fabric.

  • Build reporting-ready datasets through data cleansing, transformation, and validation.

  • Develop scalable data models that support reporting and analytics.

  • Write and optimise complex SQL queries for analytics and reporting.

  • Work with Lakehouse, Delta Lake, and enterprise data platforms.

Data Quality & Governance

  • Ensure data accuracy and consistency within reporting solutions.

  • Support data governance and data quality initiatives.

  • Maintain documentation for datasets, reports, and business rules.

  • Assist in monitoring and improving data quality processes.

Collaboration

  • Collaborate with business users, product owners, and technical teams.

  • Contribute to BI development standards and best practices.

  • Participate in solution design discussions and continuous improvement initiatives.

  • Share knowledge and support other team members where appropriate.

Required Technical Skills

Microsoft Data Platform

  • Microsoft Fabric

  • Power BI

  • Azure Synapse Analytics (Microsoft SQL Server)

  • Azure Data Factory

  • OneLake

  • Lakehouse Concepts

Business Intelligence

  • Advanced Power BI

  • DAX

  • Power Query (M)

  • Semantic Models

  • Tabular Models

  • Power BI Report Builder

  • Dashboard Design

Data Engineering

  • SQL (Advanced)

  • PySpark

  • Python

  • Data Modelling

  • ETL / ELT

  • Data Warehousing Principles

Analytics

  • KPI Development

  • Trend Analysis

  • Data Analysis

  • Data Storytelling

Development Practices

  • Git

  • Version Control

Preferred Skills

  • Experience working with Microsoft Fabric analytics solutions.

  • Exposure to Delta Lake.

  • Exposure to CI/CD practices.

  • Knowledge of dimensional modelling (Kimball).

  • Experience within Financial Services or Insurance.

  • Understanding of DataOps and analytics engineering practices.

  • Exposure to forecasting, predictive analytics, or machine learning concepts.

Soft Skills:

  • Strong analytical and problem-solving skills.

  • Good communication skills with technical and business stakeholders.

  • Strong attention to detail.

  • Willingness to learn and adapt to new technologies.

  • Ability to work effectively in a collaborative environment.

Education & Experience

  • Degree, diploma, or industry certification in Data Science, Computer Science, Information Systems, or a related field (or equivalent experience).

  • 4+ years of experience in Analytics Engineering.

  • Extensive experience delivering enterprise reporting and analytics solutions using Microsoft technologies.

  • Experience developing PySpark notebooks within Microsoft Fabric or Apache Spark environments.

  • Proven experience building Power BI semantic models, dashboards, and reporting solutions.

  • Strong SQL development experience.

Skills

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See also

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