Lead the evolution of a modern data platform by overseeing the design and operation of scalable data pipelines and cloud infrastructure. As Head of Data Engineering, you will manage a team of data, analytics, and machine learning engineers, fostering a culture of technical excellence, ownership, and continuous improvement.
Key Responsibilities
- Provide strategic direction for data engineering initiatives, aligning people, processes, and technology with broader business and technology objectives.
- Translate business requirements into actionable technical roadmaps, ensuring data platforms support AI-driven growth and internal system modernization.
- Oversee the development and maintenance of cloud-based data systems built on Snowflake and Azure, leveraging tools like DBT, Airflow, and Terraform for automation and reliability.
- Ensure data solutions meet performance, security, and compliance standards across the development lifecycle.
- Collaborate with Product and Engineering teams to deliver roadmap commitments using agile methodologies.
- Manage team capacity, project planning, and budgeting while holding third-party vendors accountable to service-level agreements.
- Establish and enforce data governance frameworks, including data quality, metadata management, classification, and access controls.
- Ensure compliance with data privacy regulations such as GDPR and POPIA through documented policies and close coordination with legal and security teams.
- Stay current with emerging technologies and industry trends to maintain a competitive edge in data infrastructure and analytics capabilities.
Qualifications
- Degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field.
- 8–10+ years of hands-on experience in data engineering, with deep knowledge of ELT, data architecture, and cloud-based platform scalability.
- Proven leadership in migrating and optimizing data stacks with minimal disruption.
- Experience deploying data products that improve business efficiency through data activation and machine learning operations.
- Strong understanding of data privacy laws and governance frameworks, with demonstrated success implementing compliant data practices.
- Experience working in agile environments and collaborating with product and analytics teams.
- Familiarity with Snowflake, Azure, DBT, Kafka, and infrastructure-as-code tools such as Terraform is essential.
Preferred Background
- Master’s degree in a relevant field.
- 3–5 years in a leadership role managing data engineering, compliance, or governance functions.
- Experience in financial services or banking environments.
- Prior success in defining and executing enterprise data strategy.
