What You'll Do
Lead and develop a team of data, analytics, and machine learning engineers, promoting a culture of accountability, innovation, and technical excellence. Provide clear direction, career growth opportunities, and hands-on mentorship.
Shape and execute the organization’s data strategy, aligning people, processes, and technology with broader business and technical objectives. Translate business needs into actionable technical roadmaps, particularly around AI-driven initiatives and platform modernization.
Oversee the design and operation of scalable data pipelines and cloud-based infrastructure, ensuring performance, security, and reliability. Use tools like Snowflake, Airflow, and DBT to build and maintain robust data systems.
Ensure adherence to data governance, privacy, and compliance standards. Collaborate with legal and compliance teams to implement policies around data access, retention, and classification, staying current with regulations such as GDPR and POPIA.
Manage vendor relationships and third-party suppliers, ensuring service levels are met. Contribute to the Technology Management team, helping align data initiatives with company-wide goals.
Requirements
- Hold a degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field.
- Have 8–10+ years of hands-on experience in data engineering, with deep knowledge of data architecture, ELT workflows, and CI/CD practices.
- Demonstrate experience building and managing cloud-based data platforms at scale, particularly on Azure.
- Show a history of leading data stack migrations with minimal disruption and strong performance outcomes.
- Have worked closely with analysts in data mesh or lakehouse environments, balancing empowerment with governance.
- Possess strong familiarity with data privacy laws and real-world implementation of compliance programs.
- Bring proven experience developing data governance frameworks, including metadata management, data quality, and stewardship models.
- Be experienced in agile environments and cross-functional collaboration with product and engineering teams.
Preferred Qualifications
- A master’s degree is a plus.
- 3–5 years in a leadership role managing data engineering, governance, or compliance functions.
- Hands-on experience with Snowflake, Azure, and DBT Cloud/Core.
- Experience defining and executing enterprise data strategy.
- Background in financial services or banking is beneficial.
Technical Environment
Our stack includes Snowflake, Azure, AzureSQL, Postgres, Airbyte, Apache Airflow, change data capture (CDC), event streaming (Kafka or similar), DBT, and Terraform. Machine learning operations are supported through Azure ML.
