Data Warehouse Engineer

Overview

Johannesburg, South Africa | Posted on 04/05/2026

Location: Johannesburg | Work Type: Hybrid | Job ID: J107172

About our client

Our client offers financial service solutions helping their clients achieve their dreams. With an emphasis on culture fit, they boast a dedicated team of over 600 employees, many with over a decade of tenure. They have built their culture on a feeling of togetherness, trust and respect and are always looking to support employees\' continuous learning. Using Agile, they provide diverse services with a focus on research, innovation and improvement.

What you will be doing

• Design, implement, and maintain scalable data warehouse architectures (Star/Snowflake) and optimize ETL/ELT pipelines for data quality.
• Write and tune complex SQL (T-SQL/ANSI) and use Python for data manipulation and advanced analytics.
• Own the full SDLC: requirements, design, testing, deployment, and solution estimation.
• Collaborate with stakeholders to translate business data needs into technical structures.
• Identify and resolve performance bottlenecks through normalisation, indexing, and query optimization.
• Develop and maintain dashboards/reports using tools like Power BI or Yellowfin for data-led decision-making.
• Create and maintain high-quality technical documentation (data flow diagrams, specifications, metadata).
• Actively participate in the Agile/Scrum framework and sprint ceremonies.
• Research and evaluate emerging data technologies to continuously improve the data warehouse.

What our client is looking for

• A relevant tertiary qualification would be beneficial (Computer Science, IT, Data Science, etc.)
• Strong knowledge of analytical & dimensional data warehouse modelling, design, architecture, data structures, and fundamental design principles.
• Experience in developing and modifying ETL processes (Extract, Transform, Load) using various data sources, and understanding concepts like data normalisation and performance tuning.
• Proficiency in relational databases (SQL Server, PostgreSQL), SQL (TSQL/ANSI), and programming languages like Python.
• Capability in the full Software Development Life Cycle, including solution estimation, requirements gathering, analysis (modifying data structures to meet client needs), technical design, unit testing, debugging, and documentation.
• Ability to consult with clients to gather requirements, analyse business needs, propose technical alternatives, and provide necessary documentation (e.g., technical specifications, data flow diagrams).
• Understanding of Big Data Visualization Tools and specific industry BI Visualization tools (e.g., Yellowfin or Power BI).
• Essential skills include communication (verbal & written, internal & external), problem-solving, and being a team player.