Our client, a leading bank based in Sandton, is seeking an experienced Analytical Engineer to join their enterprise data team on a 12-month contract. This role is ideal for a data professional who combines strong Data Engineering, Data Analysis, and Data Modelling expertise and enjoys transforming complex business requirements into trusted, analytics-ready data solutions.

The successful candidate will play a key role in enabling enterprise reporting, analytics, and data-driven decision-making by designing scalable data models, building robust data transformation pipelines, and ensuring data quality and governance standards are maintained.

Key Responsibilities

Data Modelling & Design

• Design and implement scalable Data Vault 2.0 and Dimensional Data Models to support reporting and analytics requirements.
• Ensure alignment with enterprise data architecture, modelling standards, and best practices.
• Develop reusable and sustainable data structures that support business and regulatory requirements.

Data Engineering & Transformation

• Develop and maintain ETL/ELT processes to ingest, cleanse, transform, and integrate data from multiple source systems.
• Deliver curated, analytics-ready datasets for business intelligence, reporting, and advanced analytics.
• Optimise data pipelines and data processing performance within enterprise data platforms.

Analytics Enablement

• Partner with business stakeholders, analysts, and data scientists to deliver trusted data assets.
• Perform data profiling, validation, and analysis to ensure accuracy and reliability.
• Support data-driven decision-making through the provision of high-quality data products.

Data Governance & Quality

• Ensure data integrity, consistency, lineage, and auditability across data assets.
• Apply enterprise data governance frameworks and quality controls.
• Support compliance with banking, regulatory, and governance requirements.

Stakeholder Engagement

• Collaborate with business and technical stakeholders to understand requirements and translate them into effective data solutions.
• Participate in Agile delivery teams and contribute to enterprise data product initiatives.
• Bridge the gap between business requirements and technical implementation.

Minimum Requirements

Proven experience in Data Modelling, including:

o Data Vault 2.0

o Dimensional Modelling (Kimball Methodology)

Advanced SQL skills for data transformation, optimisation, and analysis.

Strong Python experience for data engineering and analytics.

Experience working with modern cloud data platforms such as:

o Azure

o Databricks

o Microsoft Fabric

Strong understanding of:

o Enterprise Data Warehousing

o ETL/ELT Processes

o Data Pipelines

o Analytics and Reporting Solutions

• Experience with data governance, data quality frameworks, lineage, and metadata management.
• Strong stakeholder engagement and communication skills.
• Experience working within Agile delivery environments.

Preferred Experience

• Banking or financial services industry experience.
• Exposure to real-time or streaming data processing frameworks.
• Knowledge of DataOps, DevOps, and CI/CD practices.
• Relevant certifications in Data Modelling, Azure, Databricks, Microsoft Fabric, or Cloud Data Engineering.

If you have a passion for data, enjoy solving complex business problems, and possess strong data modelling and analytical engineering capabilities, we encourage you to apply.