Management Level
Manager
Job Description & Summary
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member’s unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
- Analyse and identify the linkages and interactions between the component parts of an entire system.
- Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
- Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
- Develop skills outside your comfort zone, and encourage others to do the same.
- Effectively mentor others.
- Use the review of work as an opportunity to deepen the expertise of team members.
- Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
- Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
Position Overview:
The Data Engineer is accountable for developing and maintaining the organisation’s centralised enterprise data workflows. These workflows facilitate the automated sourcing, transformation, and delivery of data to consumers including global and local applications, data models, and reporting functions. A Senior Data Engineer demonstrates advanced technical expertise, a strong track record of successful project delivery, and the ability to contribute both independently and as an expert within teams. Based on seniority, the engineer may be assigned responsibility for complex projects with significant financial implications and associated risk to the firm.
Culture Vision Statement:
Our Africa Tech team is a dynamic community of self-starters and innovators who embrace change and the constant evolution of technology. We are committed to fostering an environment where curiosity thrives and creativity is celebrated. By leveraging AI-assisted tools and respecting diverse perspectives, we drive collaborative success while enhancing our collective knowledge and skills. We believe in the power of technology to transform and improve our processes, always seeking to challenge the status quo. Together, we work with urgency and empathy, united in our mission to create impactful solutions that benefit our firm and our clients.
Key Responsibilities:
Data Pipeline Development
- Building and maintaining data pipelines that collect data from source systems, store the data within the Africa Data Warehouse, and process the data efficiently.
- Build data end points that provision data for consumers and applications, both locally and globally.
- Ensure that provisioned data is standardised and consistent in line with the enterprise data catalogue definitions.
- Ensure that deployment of code is done through approved DevOps pipelines and follows the development, staging and production lifecycle.
- Ensure ongoing review and maintenance of pipelines to meet changing business and data rules and requirements and run efficiently.
Data Aggregation: Summarizing detailed data into higher-level insights, such as calculating averages, totals, or other statistical measures.
Data Modelling
- Designing, constructing, and managing data models to ensure data can be referenced and related in a manner that supports business operations and processes.
- Creating high-level (Conceptual) models that outline the overall structure of the data and how different data elements relate to each other.
- Developing detailed (Logical) models that define the data elements, their attributes, and the relationships between them.
- Translating logical models into physical models that specify how the data will be stored in databases, including tables, columns, data types, and indexes.
- Mapping out how data moves through different systems and processes within the organization using data flow diagrams.
Technical Mentorship and Training
Qualifications and Skills:
Education:
Travel Requirements
Up to 20%
Available for Work Visa Sponsorship?
No
Job Posting End Date
August 10, 2026
