Data Engineer; Full Stack

We are seeking an experienced Data Engineer (Full Stack) to join a dynamic data team responsible for building and maintaining modern data platforms, pipelines, and analytics solutions. This role requires an engineer who can own the data lifecycle end-to-end, from ingestion and transformation through to data modelling and analytics enablement.

As a Full Stack Data Engineer, you will be responsible for designing, developing, and optimising scalable data solutions that support business intelligence, advanced analytics, and machine learning initiatives.

You will work across the entire data value chain, ensuring that high-quality, trusted, and well-structured data is readily available for reporting, analytics, and operational decision-making.

Design, develop, and maintain robust data ingestion pipelines.

Build scalable ETL/ELT processes from multiple source systems.

Monitor and optimise data integration processes to ensure reliability and performance.

Troubleshoot and resolve data pipeline issues.

Design and implement data warehouse solutions and data marts.

Develop dimensional models and data structures aligned with business requirements.

Ensure data quality, consistency, and governance standards are maintained.

Optimise data models for performance and scalability.

Develop and manage semantic data models that support self-service analytics.

Create curated datasets for reporting and business intelligence consumption.

Collaborate with analysts and business stakeholders to deliver trusted data assets.

Prepare clean, performant, and reusable datasets for dashboards, reporting, and downstream analytical or machine learning use cases.

Support the development of data products that drive business value.

Ensure data assets are well-documented and maintained.

Participate in solution design, development, testing, deployment, and support activities.

Perform code reviews and contribute to development best practices.

Create and maintain technical documentation.

Work closely with Data Engineers, Data Analysts, Data Scientists, and business stakeholders.

Participate in Agile ceremonies and sprint activities.

Share knowledge and mentor junior team members where required.

Contribute to continuous improvement initiatives across the data platform.

4-6 years' experience in Data Engineering and Data Warehouse development.

Proven experience designing and implementing ETL/ELT solutions.

Experience with dimensional modelling and data warehousing concepts.

Strong understanding of data integration and pipeline architecture.

Experience working with cloud data platforms, including:

AWS

Experience with relational databases such as:

SQL Server

Oracle

MySQL

Programming experience in:

Python

SQL

Java (advantageous)

Shell scripting (advantageous)

Knowledge of source control tools such as Git.

Understanding of software development lifecycle (SDLC) principles.

Experience working within Agile environments.

Experience supporting modern analytics platforms.

Exposure to semantic modelling and analytics engineering practices.

Experience with BI and data visualisation platforms.

Experience building datasets for reporting, analytics, and machine learning solutions.

Retail industry experience would be advantageous.

Bachelor's Degree in Computer Science, Information Systems, Engineering, or a related field.

Relevant cloud and data certifications will be advantageous.

Strong problem-solving and analytical skills.

Excellent communication and stakeholder engagement abilities.

High attention…