Data Engineer

We are looking for a Data Engineer who takes pride in building data infrastructure that actually works — reliably, at scale, and in production. This is a hands-on engineering role where you will design and deliver the pipelines, data models, and workflows that power analytics, AI, and business decision-making across the organisation.

If you care about data quality, clean architecture, and engineering that stands up under pressure, this role is for you.

What You'll Be Doing

• Design, build, and maintain scalable data pipelines and data stores supporting analytics, reporting, and operational use cases

• Develop and optimise ingestion, transformation, and orchestration workflows across structured and unstructured data sources

• Embed data quality, lineage, reliability, and security controls throughout the engineering lifecycle

• Collaborate with analysts, data scientists, and business stakeholders to translate requirements into robust data models and reusable datasets

• Monitor and troubleshoot data jobs, improve pipeline performance, and support production operations and incident resolution

• Contribute to technical documentation, coding standards, and deployment and testing automation

What We're Looking For:

• Strong proficiency in SQL and data modelling — you can design and optimize schemas for performance and scalability

• Hands-on experience building ETL/ELT pipelines — from ingestion through transformation to delivery

• Solid Python skills and practical experience with cloud data platforms (AWS, Azure, or GCP)

• Minimum 2 years of experience in a data engineering or closely related role

• Bachelor's Degree in Computer Science, Information Systems, Data Science, or a relevant field

Good to have:

• Experience with Spark or distributed data processing frameworks

• Familiarity with data warehousing and data lake concepts and architectures

• Understanding of data governance, security practices, and CI/CD pipelines for data workflows