Location Data Lead - (AD-L8.5) at Zutari

Role overview

• 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
• MQTT / SCADA / industrial IoT protocols (e.g. Sparkplug B, OPC-UA, Modbus)
• Streaming and real-time pipeline experience (Kafka, Spark Streaming, or similar)
• Experience working with time-series data and/or IoT data streams (e.g. InfluxDB, TimescaleDB, or similar)
• Familiarity with geospatial data and tools (e.g. GeoPandas, PostGIS, or similar)