We are seeking an experienced Lead Data Engineer / Technical Data Manager to drive data engineering practices and support enterprise data governance initiatives across the organisation. This role will work closely with the CTO and cross-functional engineering teams to ensure data is structured, secure, and governed consistently across applications, databases, and APIs.
The successful candidate will lead the design and implementation of scalable data architectures, enforce data quality controls, and promote best practices in UI data validation, API schema enforcement, and database design to improve data reliability and analytics readiness.
Key Responsibilities
- Lead the design and implementation of data engineering frameworks, data models, and data pipelines to support enterprise applications and analytics.
- Work with the CTO and Data Governance stakeholders to implement and operationalise data governance policies, including data quality controls, data lineage, and master data management practices.
- Establish and enforce data engineering standards across the organisation covering:
-Database schema design
-API schema validation and integration patterns
-Data security and access controls
-Data lifecycle management and retention policies
- Collaborate with application development teams to ensure UI/UX data entry controls such as required fields, structured inputs, dropdown lists, and validation mechanisms are implemented to improve data quality.
- Lead data modelling and database optimisation efforts, ensuring scalable, performant, and well-structured schemas that support operational systems as well as analytics and AI workloads.
- Establish processes to monitor data quality, detect anomalies, and track accountability for data entry and modification across systems.
- Ensure enterprise data is securely managed, implementing best practices in data classification, encryption, access control, and audit logging.
- Work with engineering teams to integrate data observability, logging, and monitoring into applications and data pipelines.
- Promote adoption of AI-ready data practices, ensuring structured, consistent, and high-quality datasets suitable for analytics, machine learning, and business insights.
Requirements
- 47 years of experience in data engineering, backend engineering, or technical data architecture roles.
- Strong experience in database design and data modelling (e.g., relational databases such as SQL Server, PostgreSQL, or Azure SQL).
- Practical experience working with APIs, integration patterns, and API schema standards such as OpenAPI / JSON schema.
- Strong understanding of data governance principles, including data quality management, master data management, and data lifecycle management.
- Experience working with cloud platforms such as Azure or AWS, particularly in relation to data services and secure data architectures.
- Familiarity with data security practices, including data access control, encryption, and audit logging.
- Ability to collaborate with engineering, product, and business teams to translate governance requirements into practical engineering solutions.
- Strong analytical thinking, documentation skills, and the ability to define technical standards and best practices.
- Experience supporting data analytics, reporting platforms, or AI initiatives will be an advantage.
- Ability to work independently, take ownership of data engineering practices, and support enterprise-wide data initiatives.
