Reconciliation Oversight Specialist

Ninety One is an independent, active global asset manager with R3,9 trillion * of assets under management.

Established in South Africa in 1991, as Investec Asset Management, the firm started offering domestic investments in an emerging market. In 2020, almost three decades of organic growth later, the firm demerged from Investec Group and became Ninety One.

Our distinctive capabilities sit within differentiated fixed income and credit as well as specialist equities, and we have a unique perspective and approach to investment opportunities presented by emerging markets and the energy transition.

*as at 31 March 2026

Ninety One is an equal opportunities employer. Our imperative is to attract and retain the best talent by providing a corporate environment where people from varying backgrounds can develop professionally and build a rewarding career.

For an Investment Management firm, data is critical to everything we do and powers the decisions we make. Accurate data, made available in a timely and easily accessible way to our data-hungry consumers, is key to our success.

We are looking for a skilled, curious, and passionate Data Engineer to help drive the evolution of our enterprise data platform. You will play a key role in delivering trusted data products that enable investment, operational, and client-facing decision-making across the firm. Working across the full data lifecycle, from ingestion and transformation through to trusted consumption, you will help ensure our data is reliable, scalable, and fit for purpose.

The role is hands-on and will suit an engineer with experience designing, building, and operating modern data platforms in production environments. You will work with structured and unstructured data, implement robust data pipelines, and contribute to data quality, governance, and observability practices that ensure confidence in our data products.

We have a strong preference for industry-standard cloud technologies, particularly Microsoft Azure and its associated services. You will work with modern cloud-native tooling, CI/CD best practices, Infrastructure-as-Code, and scalable data architectures that support the firm's growing data needs.

The data engineering discipline is evolving rapidly, and we are excited by the opportunities presented by AI and emerging technologies. We are looking for someone who is curious about where the industry is heading, actively explores new approaches, and can apply technology thoughtfully to improve productivity, engineering quality, and business outcomes.

You will be a key member of an evolving Technology team responsible for both the day-to-day operation of critical data platforms and the delivery of strategic initiatives that support our vision of being a Technology-Enabled and Data-Literate firm.

We are not a siloed organisation; we work collaboratively across technology, investment, operations, and client teams to deliver the best outcomes for the firm.

• Own data products from ingestion through to trusted consumption, ensuring data is reliable, accessible, and fit for purpose.
• Design, build, and operate scalable ELT and ETL pipelines across structured and unstructured data sources.
• Develop and maintain modern cloud-based data platforms using industry-standard engineering practices and tooling.
• Implement data quality, governance, and observability capabilities to ensure trust in our data products.
• Deliver data solutions through CI/CD pipelines and Infrastructure-as-Code, contributing to a robust and maintainable engineering ecosystem.
• Evaluate and apply emerging technologies, including AI and LLM-based tooling, to improve engineering productivity and business outcomes

• A degree in Computer Science, Engineering, Mathematics, Science, or a related quantitative field.
• At least four years of experience building, deploying, and operating data pipelines in production environments.
• Strong Python and PySpark skills, with a solid understanding of modern data engineering practices.
• Hands-on experience with a major cloud platform such as Azure, AWS, or GCP.
• Experience building and maintaining CI/CD pipelines using tools such as Azure Pipelines, GitHub Actions, or Jenkins.
• A curious, self-driven mindset, with an interest in AI, emerging technologies, and continuously improving the way data engineering is done.

• The ability to build and maintain meaningful relationships
• The ability to ‘approach and own’ and continuously look for opportunities to develop
• A strong belief in doing the right thing
• Ability to recognise and embrace change

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