Senior Data Engineer

Pwc South Africa; Johannesburg; On-site; ZAR 200 000 - 300 000; Full time

Job summary

A consulting firm in Johannesburg is seeking a Senior Data Engineer. This full-time role involves developing data models, maintaining data quality, and mentoring junior staff. The ideal candidate will have 8–10 years of experience in cloud data engineering, with strong skills in SQL, Python, and data modeling tools. The position emphasizes collaboration, innovation, and adherence to security standards.

Qualifications

• Minimum of 8–10 years of experience in cloud data engineering or related roles.
• Ability to mentor junior staff and develop training materials.

Responsibilities

• Build and maintain data pipelines for data collection and processing.
• Ensure data is standardized and consistent as per enterprise data definitions.
• Maintain high data quality through validation methods and monitoring.
• Implement data governance and security policies.

Skills

SQL

T-SQL

SSIS

SSAS

Database security

Database monitoring

Data modelling

Python (Pyspark)

Power BI

Machine learning (understanding)

Education

Bachelor Degree in Computer Science

Certifications in Microsoft Azure Synapse

Certifications in Microsoft Databricks

Job description

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

• 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 raw data into formats that meet consumer requirements and / or are useful for analysis, that may involve cleaning and wrangling the data.
• Data Cleaning: Removing or correcting errors, inconsistencies, and duplicates in the data to ensure its accuracy and reliability.
• Data Normalization: Standardising 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 Aggregation: Summarising detailed data into higher‑level insights, such as calculating averages, totals, or other statistical measures.
• Data Integration: Combining data from various sources into a unified set, making it easier to analyse and derive insights.
• Data Formatting: Converting data into the required format for analysis or reporting.
• Ensuring that standard calculations are applied in line with data catalogue definitions.
• Ensuring ongoing review of transformation calculations to align with changing business and data rules.
• 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.

Data Quality Assurance

Ensuring the accuracy and integrity of data by developing validation methods and monitoring data quality. Ensuring that all deployed workflows meet the Definition of Done and have undergone peer review before being deployed to staging and production environments. Ensuring that all data deliverables meet the business requirements as outlined in the acceptance criteria. Ensuring robust, optimised data solutions by applying techniques such as stress testing. Ensuring that test tasks and results are recorded and confirmed.

Security and Compliance

Understanding of data governance and security policies and the application of secure coding principals to protect sensitive information. Adherence to PwC data design and development standards. Ensuring that accurate technical documentation is maintained. Ensuring that security by design is implemented. Ensuring that the concept of least privileged access to data and minimisation of data is applied. Ensuring that data privacy techniques are applied such as data anonymisation, aggregation and de‑identification. Ensuring that data is encrypted in transit and at rest. Ensuring that appropriate change and release processes are followed. Working with product teams and LoS stakeholders to understand data needs and ensure data is accessible and usable. Attend design session to provide input into data requirements for solutions. Develop technical designs and technical steps to meet data requirements and provide timelines that feed into overall project delivery. Engage with local and global technical teams to determine dependencies and incorporate timelines and dependency steps into delivery considerations and timelines.

Technical Mentorship and Training

Act as a mentor to junior staff within the team. Provide input into the development of technical training curriculums. Provide technical input into data communities of interest and practice.

Qualifications and Skills

Education

Bachelor Degree in Computer Science or equivalent relevant work experience.

Certifications

Certifications in Microsoft Azure Synapse.

Certifications in Microsoft Databricks.

Experience

Minimum of 8–10 years of experience in cloud data engineering or related roles within a complex organisational environment.

Technical Skills

• SQL
• T‑SQL
• SSIS
• SSAS
• Database security
• Database monitoring
• Data modelling
• Python (Pyspark)
• Power Bi
• Machine learning (understanding)

Conclusion

At PwC, our purpose is to build trust in society and solve important problems. As we navigate an increasingly complex world, we are dedicated to ensuring that the systems on which communities and economies depend can adapt and thrive. Each role within our organization contributes to this mission, reinforcing our commitment to high ethical standards and the importance of trust. Our five core values guide our actions and define who we are. They emphasize building trust through professionalism, ethical behaviour, and the commitment to quality in all our interactions, whether with clients, colleagues, or the broader community. We respect privacy and confidentiality, and we strive for transparency in our operations, demonstrating care and integrity in our relationships. As part of our human‑led, tech‑powered approach, we empower our people through technology and foster an environment where speaking up is encouraged, and diverse perspectives are celebrated. By embodying these principles in our daily work, we can collectively drive impactful outcomes that resonate with our clients and society as a whole. Together, let's embrace our purpose and values to create meaningful change.

Senior Data Engineer Role

The Senior Data Engineer is essential in developing data models for provisioning, ensuring trust in our data, generating revenue through data monetisation, and maintaining the quality and integrity of the organization's data assets. Your deep knowledge of data engineering practices and dedication to promoting a culture of accountability will greatly enhance the effectiveness of data provisioning initiatives within PwC Africa. A strong passion for data engineering, cloud solution architecture, and alignment with PwC's purpose are crucial for success in this role.

Seniority level

Mid-Senior level

Employment type

Full‑time

Job function

Information Technology

Industries

Business Consulting and Services

Location

Johannesburg, Gauteng, South Africa