Senior Analytics Engineer (Contract)

Introduction 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.

Duties & 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 documentation 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.

Desired Experience & Qualification

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.