Data Lead - Bryanston/Centurion

SUMMARY:
Our client in the automotive and data industry is seeking to employ a Data Lead – Auto to join their team based in Bryanston/Centurion, with a hybrid working model.

Exciting Opportunity:
Join a high-growth, data-driven environment where you will provide technical leadership and drive the delivery and evolution of data capabilities within the automotive business. This is an opportunity to lead experienced data professionals, work with rich and unique data assets, and contribute to innovative, commercially valuable data products.

POSITION INFO:
Requirements:

• Relevant degree in Data, Engineering, Computer Science, Business or a similar field.
• 10–15+ years’ experience in data-related roles.
• 5+ years’ experience in Data Management Leadership roles.
• Strong experience across data platforms, data engineering and/or data architecture.
• Proven experience in data governance, data quality and regulatory compliance.
• Experience developing data products within commercial environments.
• Strong stakeholder collaboration, engagement and advisory skills.
• Experience implementing data strategies and operating models aligned to business needs.
• Strong understanding of end-to-end data lifecycle management, including retention, archiving and deletion.
• Strong understanding of modern data architectures and integration patterns, including ETL/ELT and APIs.
• Experience across on-premises and cloud environments.
• Proficiency in SQL-based environments.
• Experience with data pipeline development, automation and performance optimisation.
• Understanding of POPIA and other applicable regulatory requirements.
• Ability to translate data into commercially valuable products and client-facing solutions.
• Experience working across technical, business and regulatory stakeholders.
• Automotive, mobility, financial services or consumer data experience advantageous.
• Knowledge of AI/ML concepts and advanced analytics advantageous.
• Strong problem-solving and analytical skills with excellent attention to detail.
• Excellent communication and teamwork skills, including the ability to communicate effectively with non-technical stakeholders.
• Strong relationship-building and networking capabilities.
• Ability to manage multiple priorities and conflicting demands effectively.
• Strong client service and expectation management skills.
• Passion for continuous learning and expanding technical knowledge.
• Ability to embrace and initiate change within an agile and fast-paced environment.
• Strong ownership, initiative and outcome-driven approach.
• Sound judgement, resourcefulness, adaptability and resilience.

• Lead the design, development and optimisation of data pipelines, models and platforms.
• Translate business requirements into scalable, efficient and maintainable data solutions.
• Provide technical leadership and guidance to data engineers and analysts.
• Ensure data solutions are well structured and aligned with technical best practices.
• Design and implement data architectures, including data marts, integration layers and APIs.
• Ensure efficient data ingestion, transformation and integration across systems.
• Contribute to platform evolution through performance optimisation and scalability improvements.
• Implement and maintain data quality controls, validation processes and monitoring.
• Ensure the reliability, accuracy and availability of critical datasets.
• Identify and resolve data issues while continuously improving data processes.
• Implement and uphold data governance practices across relevant data domains.
• Support data classification, retention and lifecycle management processes.
• Ensure compliance with applicable regulations, including POPIA and PAIA, as well as internal policies.
• Collaborate closely with Product, Business and Engineering teams.
• Translate complex data and technical concepts into clear and practical insights for stakeholders.
• Support internal and client-facing initiatives requiring data expertise.
• Lead and mentor a team of data engineers and analysts.
• Support team development through coaching, knowledge sharing and technical guidance.
• Foster a culture of ownership, quality and continuous improvement.
• Stay informed about emerging data technologies, architectures and practices.
• Identify opportunities to improve data capabilities, tools and processes.
• Enhance the efficiency, scalability and usability of data solutions.
• Contribute to the development of innovative and commercially valuable data products.
• Support the practical application of AI/ML and advanced analytics where relevant to business challenges.