Zutari's Digital Practice team is expanding its data practice and requires a location lead in Tshwane. The team delivers innovative solutions across the business for internal and external clients across various industries e.g. energy, transport, water, and buildings.
Working at the intersection of engineering and technology, the team partners with multi-disciplinary engineering teams, BIM and IoT specialists to connect static 3D and asset data with real-time information to help clients solve interesting and complex problems.
Role responsibilities
Lead and build a data team in Tshwane with assistance from the Zutari Data Lead.
Collaborate across cross-functional teams to deliver multiple concurrent data and analytics projects.
Ingest and consolidate raw data from diverse sources, including Building Information Modelling (BIM), IoT sensors, and ERP systems.
Design, build, and maintain scalable data architectures and end-to-end data pipelines.
Perform data analysis and develop BI analytical tools to surface actionable insights for stakeholders.
Research, prototype, and validate machine learning and AI proof-of-concepts to address business challenges.
Minimum requirements
Leadership experience leading data professionals
A "can-do" attitude and genuine passion for applying data in engineering and infrastructure domains
Bachelor's degree in Engineering, Computer Science, or a related field
At least 8 years' experience in data engineering and/or data science
At least 2 years leading a team
Fluent in Python and GIT version control
Hands-on experience with SQL databases, data warehousing, and data pipeline design
Ability to communicate complex technical findings clearly to non-technical engineering stakeholders - both in writing and in presentations
Comfortable leading technical decisions on a workstream and collaborating across multidisciplinary teams (BIM, IoT, engineering, business functions)
Advantageous
Master's or higher qualification
Experience in infrastructure sectors (energy, water, transport, or buildings)
Understanding of asset lifecycle data and digital twin concepts, including semantic data modelling or ontologies
Software development experience
Experience with Docker for containerisation and deployment of data applications
Experience with BIM data formats (IFC) or integration with BIM platforms
Data engineering certification
Software development and software engineering best practices
Leveraging Claude Code (or similar) to increase output
Proven experience building and deploying ML/AI solutions beyond proof-of-concept
Cloud and data platform experience: Snowflake, Microsoft Fabric, Databricks, BigQuery, or similar