Data Engineering Lead

Position Overview:

The Technical Lead is responsible for the development and delivery of Cloud technical data solutions that support enterprise data management and data usage requirements. The Lead ensures that all technical data services and solutions are designed and implemented according to best practices and support firm regulatory business enablement requirements. The Cloud data solutions should enable robust use of Artificial Intelligence and Machine Learning. The Technical Lead coordinates delivery of technical solutions across Data Engineering and Data Infrastructure services and engages with stakeholders to ensure that deliverables meet the business strategy and requirements within the agreed timelines.

Culture Vision Statement:

Our Africa Tech and Digital 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:

1. Technical Data Strategy:

• Implement technology that aligns with the business strategy and fulfills business and network requirements for data services.

• Engagement and collaboration with internal and LoS technical teams to ensure alignment awareness and adoption of technical data solutions and services in support of business requirements.

• Forecast technology trends be able to proactively Identify technology pivots and roadmap. Evaluate new approaches technologies and services to ensure that Data solutions and services meet changing business demand and enable innovative solutions that can be implemented with agility urgency and agency.

2. Data Modelling:

• Implement data solutions that are in line with data modelling best practices.

• Provide technical data services that meet the ongoing requirements of the business in a cost effective and efficient manner.

• Implement data solutions and services promote ethical and responsible use of data within the firm.

• Engage with local and global SMEs and teams to ensure that the technical data solutions and services adhere to standards assist the firm in meeting regulatory requirements and align to the network roadmap.

3. Technical Standards:

• Develop technical standards for each pillar of the Software Development Lfe0cycle (SDLC) in collaboration with other SMEs across AfricaTech.

• Collaborate with and assist internal and LoS teams with understanding and implementing technical standards requirements of the firm and advise on best practices.

4. Solutions Design

• Collaborate in product design sessions to provide input on technical data requirements and approaches that support the data requirements of the desired business product outcomes.

• Assist with defining technical delivery plans that will meet the requirements for data-driven solutions.

• Evaluate the delivery of data solutions to ensure that they support strategic deliver meet business requirements and adhere to technical standards.

5. Operational Management

• Act as a mentor to technical staff within the team.

• Assist with the development of technical training curriculums.

• Provide technical support and input into data communities of interest and practice.

• Assist with internal and LoS data training programmes.

7. Continuous Improvement:

• Identify opportunities to enhance data quality processes tools and techniques leveraging innovative approaches to improve overall data governance and quality strategies.

• Contribute to ongoing assessments of the effectiveness of data quality practices proposing adjustments based on industry trends and organizational needs.

• Drive the optimisation and automation of redundant and obsolete processes

• Master and champion the use of AI tools in the delivery of Data Governance and Quality processes.

Qualifications and Skills:

Education:

• Any Bachelor Degree in Computer Science or equivalent relevant work experience.

• Certifications in Microsoft Databricks.

• Experience: Minimum of 8 - 10 years of experience in cloud data engineering or related roles within a complex organizational environment.

Technical Skills:

• Experience in designing and managing data warehouses.

• Experience in ensuring data security and compliance with regulations including encryption and privacy laws.

• Data quality analysis skills.

• Strong analytical and problem-solving abilities to interpret complex data and translate business requirements into technical specifications.

• Proficiency in data mining predictive modelling and working with large datasets to uncover insights.

• Designing and implementing enterprise data management frameworks.

• Knowledge of data governance and data quality principles.

• Large-scale technical data project implementation experience.

• Ability to formulate and drive a technical data strategy and budget.

• Ability to mentor and develop technical data teams.

• Ability to facilitate broader staff training.

• Ability to explain technical concepts at all levels.

• Stakeholder engagement and strong communication skills at all levels.

• Data modelling and identification and linking of Gloden Sources

• Metadata Management

• Technical skills including:

• Azure cloud data services architecture (Synapse Purview).

• Understanding of API development (REST SOAP APIM).

• DevOps experience (task management code deployment pipeline management).

• Terraform experience.

• SQL experience.

• Python experience.

• Power BI experience.

• Alteryx experience.

• Databricks experience (ideal).

• MS Fabric experience (ideal).

• Data modeling experience.

• Phython

• Use of AI and ML within Databricks and Synapse

Soft Skills:

• Excellent communication and interpersonal skills with the ability to engage effectively with diverse stakeholders.

• Analytical and detail-oriented mindset with a proactive approach to problem solving and decision making.

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 behavior and a 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 were 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 lets embrace our purpose and values to create meaningful change.

The Data Governance and Quality Manager plays a critical role in establishing data governance frameworks that will build trust in our data open revenues for data monetization and upholding the quality and integrity of the organizations data assets. Your expertise in data governance and management practices and commitment to fostering a culture of accountability will significantly enhance the effectiveness of data governance initiatives within PwC Africa. You need to be passionate about data governance and PwCs purpose needs to resonate with you.