This role is responsible for leading the design and implementation of modern data platforms and analytics solutions for enterprise environments. The person in this position will help define technical architecture, guide delivery teams, and work closely with stakeholders to turn business requirements into scalable and practical data solutions.
Key Responsibilities
- Lead the architecture and implementation of data solutions across areas such as analytics platforms, data warehouses, data lakes, and large-scale data ecosystems
- Design and maintain conceptual, logical, and physical data models that support scalability, performance, and long-term maintainability
- Provide technical leadership to engineering teams through mentoring, solution guidance, and review of development quality
- Partner with business and project stakeholders to translate functional requirements into technical designs and implementation approaches
- Oversee end-to-end project execution, ensuring deliverables, priorities, and timelines are effectively managed
- Define and promote best practices in data engineering, modelling, governance, and development standards
- Serve as a senior technical point of contact for stakeholders when resolving issues or addressing complex technical topics
- Support continuous improvement by exploring new technologies, methods, and ways to strengthen the team's delivery capability
Requirements
- Degree or diploma in Computer Science, Information Technology, or a related field
- 5+ years of relevant experience in data engineering, data warehousing, analytics platforms, data lakes, or big data environments, including experience leading or managing technical teams
- Strong knowledge of data modelling methodologies such as dimensional modelling, Kimball, star schema, snowflake schema, Data Vault, and third normal form
- Experience optimizing data structures and queries for performance across different database platforms
- Proven experience delivering enterprise-scale data projects with ownership of solution design and technical direction
- Strong hands-on skills in SQL and Python exposure to Java or Scala would be an advantage
- Demonstrated ability to lead engineers, allocate work, and develop junior team members
- Familiarity with Linux or Unix environments, as well as container technologies such as Docker or Kubernetes, is beneficial
- Good understanding of ETL/ELT concepts and experience with modern cloud data platforms such as Snowflake or similar technologies on AWS, Azure, or Google Cloud
- Exposure to data governance, data quality, or master data management would be useful
- Strong communication skills with the ability to engage both technical and non-technical stakeholders effectively
