Data Engineer

Management Level Senior Associate 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. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. 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.

Overview:   The Data Engineer is responsible for the development and support of our centralised, enterprise data workflows. These workflows automate the sourcing, transformation, and provisioning of data for consumers such as global and local applications, data models and reporting.  A Data Engineer has proven skills, ability and a delivery track record over several years and is able to work independently as well as within teams as a subject matter expert.  Depending on the level of seniority, the engineer will be given responsibility for more technically challenging projects with greater financial impact and risk to the firm.

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 Transformation   Converting   of   raw data into formats that   meet consumer requirements and/or are   useful for analysis,   that may   involv e   cleaning and wrangling   the   data.   This includes:   Data Cleaning: Removing or correcting errors, inconsistencies, and duplicates in the data to ensure its accuracy and reliability.   Data Normalization: Standardizing data formats and structures to ensure consistency across different datasets.   Data Enrichment: Enhancing data by adding relevant information from external sources, which can provide more context and value.   Data