Data Engineer (Mid-level)

About the role

About WPP Media

WPP is the trusted growth partner for the world’s leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships – all united by our pioneering agentic marketing platform, WPP Open – we help clients navigate change, capture opportunity, and deliver transformational growth.

WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.

For more information, visit wppmedia.com.

Job Title: Data Engineer (Mid-Level) Company: WPP Media South Africa Location: Johannesburg, South Africa Reports To: Senior Data Specialist

Key Responsibilites:

Data Engineering:

- Design, develop and maintain scalable ELT/ETL pipelines using modern cloud technologies.

- Build and optimise data ingestion frameworks from first-party, second-party and third-party data sources.

- Develop and maintain robust data models that support analytics and reporting.

- Build and manage integrations using REST APIs, SDKs and cloud services.

- Develop reusable data transformation frameworks using dbt or equivalent tooling.

- Implement incremental processing, partitioning and performance optimisation techniques.

- Design and maintain data warehouse structures within BigQuery and other cloud environments.

- Ensure pipeline reliability through monitoring, alerting and automated testing.

- Troubleshoot production data issues and implement long-term solutions.

Cloud Platform Engineering

- Develop scalable cloud-native data solutions on Google Cloud Platform.

- Optimise BigQuery performance and manage cloud infrastructure costs.

- Build solutions using Cloud Functions, Cloud Run, Cloud Storage and Pub/Sub where appropriate.

- Implement secure access controls using IAM principles.

- Support infrastructure automation using Infrastructure-as-Code where applicable.

- Monitor platform performance and recommend improvements.

Data Quality & Governance:

- Implement automated data validation and quality assurance processes.

- Develop and maintain metadata, documentation, and data lineage.

- Support data governance frameworks and taxonomy standards.

- Ensure compliance with data privacy, security, and governance policies.

- Establish monitoring for data freshness, completeness, and accuracy.

Analytics Enablement

- Build curated datasets that enable self-service reporting and analytics.

- Partner with Analytics Engineers, BI Developers and Data Analysts to deliver trusted datasets.

- Support dashboard development by providing clean, scalable, and well-modelled data.