What You’ll Do:

• Leadership and Strategy: Oversees the construction and maintenance of highly scalable, robust and fault-tolerant data management and processing systems. Sets the strategic direction for the data engineering team in alignment with organizational goals.
• Data Models and Architecture: Directs the team in creating and optimizing complex data models that serve as the backbone for data as a product. Sets architectural guidelines to ensure these data models meet all business requirements, reduce system complexity and are aligned with data governance policies.
• Data as a Product: Ensures that the data generated or processed is of high quality, secure and reliable enough to be considered a stand-alone product. Focuses on data usability and prepares data for analytical and operational uses, thereby creating value for business units and clients.
• ETL and Data Acquisition: Manages and directs the ETL (Extract, Transform & Load) processes,
• identifies new opportunities for data acquisition and ensures that data pipelines are secure, efficient and aligned with governance policies.
• Cost Optimization and Efficiency: Continuously reviews system efficiency and resource utilization to identify areas for cost optimization while maintaining or improving data quality and security.
• Data Security and Governance: Implements and enforces stringent data governance and security protocols, ensuring compliance with organizational and regulatory standards.
• Disaster Recovery: Manages the planning and implementation of Disaster Recovery plans and protocols, ensuring rapid data recovery while minimizing loss in the event of a failure.
• Team Development: Mentors, trains and develops team members to foster a community of data
• engineering experts who follow best practices, contribute to innovation and uphold data integrity and security.
• Cross-Functional Collaboration: Works closely with stakeholders, including product managers, business units and other technical teams, to ensure that the data engineering efforts are aligned with broader organizational goals and projects.
• Audit and Compliance: Regularly conducts audits to ensure data integrity, security and governance and coordinates with compliance teams to address any gaps or vulnerabilities.

What will ensure your success in the Role:

• Educational Background: Relevant tertiary qualifications in Computer Science, Statistics, or related technical fields.
• Extensive Experience: Proven track record in Data Modelling and Data Engineering.

Technical Proficiency:

• Expertise in data-related tools and technologies such as SQL, VBA, Python, R, Hadoop, Hive, Spark, Tableau, QlikView, and Power BI.
• Advanced SQL knowledge and experience with relational databases and query authoring.
• Familiarity with cloud technologies (AWS S3, RedShift) and integration tools (SSIS, AWS Glue, PySpark).
• Data modeling skills in SQL Server Analysis Services and Power BI.
• Analytical Skills: Ability to understand business problems and frame them into a data-driven environment.
• Data Architecture Knowledge: Understanding of data architecture, engineering methodologies, and best practices.
• Communication Skills: Excellent written and verbal skills to convey complex technical information to both technical and non-technical stakeholders.
• Problem-Solving Abilities: Strong analytical skills to tackle complex problems and lead a team in implementing solutions.
• Collaboration and Teamwork: Ability to work cohesively with colleagues and stakeholders, utilizing tools like JIRA, Lucid, and Zephyr Scale.
• Leadership and Mentorship: Experience in mentoring and developing team members, and presenting results to senior stakeholders.

Preferred Education

• Bachelors

Preferred Level of Work Experience

• 7 – 10 years