Overview

Data Technical Team Lead Jobs in Pretoria Metropolitan Area at Gap Infrastructure Corporation – GIC

Title: Data Technical Team Lead

Company: Gap Infrastructure Corporation – GIC

Location: Pretoria Metropolitan Area

The Data Technical Team Lead is responsible for the strategic and technical leadership of GIC's Data Engineering, Data Science, and Data Analytics & BI functions.

This role will design, build, and lead the implementation of GIC's enterprise data platform from the ground up – including data architecture, data structures, pipelines, governance, and analytics enablement. The incumbent must be hands-on and capable of architecting and implementing SQL/PostgreSQL-based solutions, while leading the development of a scalable Data Lake / Data Warehouse / Data Lakehouse architecture best suited to GIC's operational and strategic needs.

The Role Combines

  • Strategic data leadership
  • Deep technical architecture capability
  • Hands-on engineering competence
  • Team leadership across multiple data disciplines
  • Job Spesification

1.1 Data Strategy & Architecture

  • Define and implement GIC's enterprise data strategy.
  • Design and build a scalable, secure, and future-proof: Data Lake, Data Warehouse and Data Lakehouse architecture (based on business requirements and cost model).
  • Develop logical and physical data models across operational and analytical domains.
  • Establish enterprise data standards (naming conventions, modelling standards, metadata, etc.).
  • Implement master data management (MDM) principles where required.
  • Ensure data platform alignment with cybersecurity and ISO27001 controls.

1.2 Data Platform Engineering (Hands-On)

  • Architect and implement database environments using: SQL Server and/or PostgreSQL and Advanced SQL development (T-SQL / PL/pgSQL)
  • Design and build: ETL / ELT pipelines, Data ingestion frameworks, Data transformation layers and Data orchestration processes
  • Develop: Fact and dimension schemas (star/snowflake/databricks), Normalised operational data structures, Aggregated reporting structures
  • Implement data partitioning, indexing, performance tuning and query optimisation.
  • Establish backup, retention and disaster recovery strategies for data platforms.
  • Ensure scalability, high availability and performance of the data environment.

1.3 Data Engineering Leadership

  • Lead and mentor the Data Engineering function.
  • Establish standards for: Code management, Version control, Data pipeline development, Testing and deployment (CI/CD where applicable)
  • Oversee integration of: ERP systems, Financial systems, Project management systems and External data feeds
  • Ensure reliable and auditable data flows across subsidiaries and offices.

1.4 Data Science Enablement

  • Provide technical infrastructure and data readiness for Data Science initiatives.
  • Ensure clean, structured, and feature-ready datasets.
  • Support the deployment of predictive models into production.
  • Enable advanced analytics use cases: Forecasting, Risk modelling, Asset performance analytics and Financial trend modelling
  • Ensure compute environments support model development and deployment.

1.5 Data Analytics & BI Governance

  • Lead the Data Analyst and BI function.
  • Design and govern enterprise semantic models.
  • Ensure a "single source of truth" across reports and dashboards.
  • Define KPI governance frameworks for: Infrastructure performance, Financial metrics, Operational metrics, Executive reporting
  • Oversee BI platform architecture (e.g., Power BI or equivalent).
  • Ensure performance and data refresh optimisation.

1.6 Governance, Security & Compliance

  • Implement data governance frameworks including: Data ownership, Data classification, Access controls and Audit trails
  • Align with ISO27001 and corporate cybersecurity policies.
  • Ensure role-based access to sensitive financial and infrastructure data.
  • Maintain data quality monitoring and reporting.

1.7 Leadership & Management

  • Lead and coordinate Data Engineers, Data Scientists and Data Analysts / BI Specialists
  • Develop roadmaps and delivery plans aligned to GIC's strategic objectives.
  • Present data strategy and progress to Executive and Board level.
  • Manage vendor relationships and technology evaluations.
  • Develop budget proposals for data infrastructure investments.
  • Technical Requirements

2.1 Essential Technical Skills

  • Advanced SQL (mandatory)
  • Strong PostgreSQL experience (mandatory)
  • Data modelling (OLTP and OLAP)
  • Data warehouse design
  • Data lake / lakehouse architecture design
  • ETL/ELT pipeline development
  • Query performance tuning and optimisation
  • Indexing strategies
  • Data Analytics & BI Governance
  • Backup and disaster recovery planning
  • Experience integrating multiple enterprise systems
  • Minimum Qualifications & Experience
  • Bachelor's Degree in: Computer Science, Information Systems, Engineering or related technical field
  • 8-10+ years in Data Engineering / Database Architecture
  • 3-5+ years leading technical teams
  • Proven experience building a data warehouse or data platform from scratch
  • Demonstrated experience in PostgreSQL production environments

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