Senior Specialist Analytics & Enablement

Job Requisition ID

12953

Closing Date

31 August 2026

OME

FIN: Financial Controlling & Governance

Location

Sandton, Gauteng

Purpose of Job

The Senior Specialist Analytics and Enablement is responsible for developing, maintaining and enhancing finance data products across the Microsoft Azure Synapse data lake and adjacent analytics platforms, including Databricks where appropriate. The role translates finance and business requirements into trusted, governed and reusable data models, analytical products, reporting solutions and advanced analytics use cases that enable data-driven decision-making across the Microsoft ecosystem, including Power BI and related Power Platform tools. The position works closely with Finance, IM and business stakeholders to ensure data solutions are integrated, scalable, secure, fit-for-purpose and aligned to current and future reporting, planning, performance management and data science enablement needs.

Key Accountabilities

• Data lake and analytics platform enablement: Develop and maintain finance data products across Microsoft Azure Synapse, Databricks and related data platforms, ensuring that data is reliable, reusable and aligned to approved data architecture, engineering and governance standards.
• Data product development: Translate finance and business requirements into analytical datasets, data models, dashboards and reporting products that support performance management, planning, forecasting and decision-making.
• Integration, modelling and advanced analytics enablement: Enable integration of source data from systems such as SAP, OneStream, Excel and other relevant platforms into the finance data lake and downstream analytics environment, supporting both reporting requirements and data science use cases.
• Power BI and Microsoft ecosystem enablement: Develop and support Power BI datasets, reports, KPI scorecards and dashboards that provide clear, consistent and actionable insights to stakeholders.
• Data quality and governance: Monitor, analyse and improve data quality, master data alignment, metadata, controls and reconciliation processes to protect the integrity of finance information.
• Business partnering and insight generation: Work with Finance, IM, business units and agile delivery teams to identify opportunities, prioritise value-adding analytics use cases and convert data into practical business insight.
• Solution lifecycle management: Support the full lifecycle of analytics solutions, including requirements gathering, process mapping, design, development, testing, deployment, documentation, support and continuous improvement.
• Continuous improvement, automation and data science enablement: Identify opportunities to improve transparency, speed, standardisation and efficiency through automation, reusable data assets, modern analytics practices and targeted data science techniques.

Key Responsibilities

• Engage stakeholders to understand finance, reporting, planning and operational data requirements, and document these requirements in a clear and structured manner.
• Design, build and maintain finance data models, curated datasets, semantic models and analytical workflows in Azure Synapse, Databricks and related Microsoft technologies.
• Ingest, transform, validate and reconcile data from relevant finance and operational source systems, ensuring alignment to OneStream dimensions, Power BI modelling principles and enterprise data standards.
• Develop Power BI reports, dashboards and KPI scorecards that provide meaningful insights and support tactical and operational decision-making.
• Apply analytical and data science methods to identify trends, exceptions, risks, performance drivers, forecasts, anomalies and opportunities for optimisation across finance and business processes.
• Perform data cleansing, profiling and validation activities to ensure completeness, accuracy, consistency and usability of finance data.
• Collaborate with IM, data engineering, architecture, security and governance teams to ensure solutions are integrated, scalable, controlled and compliant.
• Participate in agile delivery activities, including backlog refinement, sprint planning, minimum viable product development, user testing and release support.
• Prepare and maintain solution documentation, data definitions, design decisions, test evidence, support material and handover artefacts.
• Support existing analytics products, dashboards, datasets and micro-solutions, resolving issues and implementing enhancements as business needs evolve.
• Advise product owners, project teams and stakeholders on data design, reporting logic, system enhancements and opportunities to leverage the Microsoft ecosystem more effectively.
• Stay abreast of emerging data, analytics and Microsoft technology trends and apply relevant practices to continuously improve the finance analytics capability.

Formal Education

• Relevant 3-4 year university degree in Finance, Accounting, Information Systems, Data Analytics, Computer Science, Engineering or a related field.
• A postgraduate qualification will be advantageous.

Working Experience

• 9+ years relevant experience in data analytics, data modelling, business intelligence, finance systems, reporting or related data enablement roles.
• Experience in finance, performance management, planning, forecasting or management reporting environments will be advantageous.

Technical Experience

• Microsoft Azure Synapse, Databricks, Azure Data Factory and related Azure data services, including data ingestion, transformation, orchestration and governed data product development.
• Power BI, including dataset modelling, DAX, reporting, dashboards and KPI scorecards.
• Proficiency in SQL and practical experience with Python or similar coding languages for data transformation, automation, analytics, data quality testing and repeatable analytical workflows.
• Experience applying data science techniques such as exploratory data analysis, feature preparation, statistical analysis, forecasting, predictive modelling or anomaly detection to practical finance or business use cases will be advantageous.
• Integration of finance and operational source systems such as SAP, OneStream, Excel and other enterprise platforms.
• Exposure to Power Apps, Power Automate, Microsoft Fabric, machine learning services or other relevant analytics and automation platforms will be advantageous.
• Understanding of finance master data, reporting hierarchies, controls, governance and data quality principles.

Certification and Professional Membership

• Azure, Power BI, data analytics, data engineering or related Microsoft certifications will be advantageous.

Required Personal and Professional Skills