The ideal candidate for this role will be responsible for designing and implementing scalable and efficient data solutions using modern data architectures. This includes developing and managing robust ETL/ELT processes and data pipelines to handle a variety of data sources and transformations. A core part of this role is to ensure the quality, integrity, and security of data across all platforms. The candidate will also support hybrid cloud deployments, seamlessly integrating both on-premises and cloud-based environments both on Azure and AWS.
In this position, the individual will collaborate closely with stakeholders to understand business requirements and provide effective technical solutions. They will also be responsible for optimizing data workflows and troubleshooting performance issues. All work must adhere to engineering best practices, including version control and modular code design, to ensure a well-documented and maintainable codebase.
Qualifications
Type of Qualification:
First Degree
Field of Study:
BSc Computer Science or Information Technology as well as Certifications in Azure or AWS
Experience Required:
Minimum 4 years' experience in Data or Software Engineering with strong hands-on experience in Azure or AWS
Advanced Proficiency in SQL and Python
Solid understanding of data modelling, data governance, and data warehousing
Experience with CI/CD pipelines or DevOps (IaaC)
Experience in MLOps and DataOps is a plus
Experience in building Data APIs
Additional Information
Behavioural Competencies:
Adopting Practical Approaches
Articulating Information
Challenging Ideas
Examining Information
Conveying Self-Confidence
Convincing People
Embracing Change
Exploring Possibilities
Producing Output
Pursuing Goals
Showing Composure
Upholding Standards
Technical Competencies:
Big Data Frameworks and Tools
Data Engineering
Data Integrity
IT Knowledge
Stakeholder Management (IT)
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