Senior Analytics Engineer

The Senior Analytics Engineer is responsible for designing and leading the development of scalable, high-quality analytics data platforms that enable advanced analytics, business intelligence, and AI use cases. This role plays a strategic function in defining data modelling standards, ensuring data reliability, and aligning analytics engineering practices with organisational data strategy.

Responsibilities


• Expert-level SQL and advanced data modelling expertise.
• Deep experience with modern data stack tools and architectures.
• Strong understanding of data pipelines, orchestration, and dependencies.
• Familiarity with software engineering best practices in data (CI/CD, testing, modular design).
• Ability to design scalable solutions to complex data challenges.
• Strong critical thinking and data validation skills.
• Proactively identifies risks, inefficiencies, and improvement opportunities.
• Define and implement analytics engineering standards, governance frameworks, and best practices.
• Lead documen tation initiatives for data models, definitions, and lineage.
• Ensure compliance with data governance, security, and regulatory requirements.
• Establish and oversee robust data quality frameworks, testing strategies, and monitoring systems.
• Ensure reliability and performance of data pipelines and analytical models at scale.
• Drive root cause analysis and resolution of complex data issues across upstream and downstream systems.

Qualifications

• Matric Bachelor's degree in Data Science, Statistics, Computer Science, Information Systems, Engineering, or related field.
• 6+ years of experience in analytics engineering, data engineering, or advanced analytics roles.
• Expert-level proficiency in SQL and extensive experience designing scalable analytical data models.
• Strong experience with data transformation tools (e.g., dbt) and modern data warehouses (e.g., BigQuery, Snowflake, Redshift).
• Deep understanding of data modelling concepts (star schema, dimensional modelling, data vault, fact/dimension design).
• Proven experience working with BI tools (Power BI, Tableau, Looker etc.) and enabling self-service analytics.
• Strong experience with version control systems (e.g., Git) and CI/CD practices in data workflows.

Advantageous

• Postgraduate qualification in a related field.
• Experience in retail, healthcare, or financial services data environments.
• Strong experience with cloud platforms (AWS, Azure, GCP).
• Exposure to machine learning pipelines and feature engineering.
• Experience mentoring or leading analytics/data teams.