Junior Data Engineer

This role combines Helpdesk support with data engineering development. You will answer and triage incoming tickets, escalating them to the correct level of support, alongside supporting the design, maintenance, and optimisation of our data pipelines and data architecture for our implemented client products and services. Working closely with data analysts, data scientists, and other stakeholders, you will help ensure the efficient and reliable flow of data across the organisation.

This position includes Out of Hours work. Standard working hours are 6:00am to 2:30pm. There may be times where further Out of Hours coverage is needed,based on a rota; an Out of Hours Allowance is provided for this.

Helpdesk & Support

Answer and triage incoming helpdesk tickets

Escalate issues to the correct level of support

Monitor the helpdesk queue and follow up on outstanding tickets and defects

Build exposure to client solution queries and investigations, bug fixes, and change controls

Data Pipeline Development

Assist in designing, building, and maintaining scalable data pipelines

Implement ETL (Extract, Transform, Load) processes to ingest data from various sources

Ensure data quality, integrity, and reliability through thorough testing and validation

Database Management

Support the management and optimisation of data storage solutions (e.g. SQL, NoSQL databases, data lakes)

Monitor and maintain database performance and security

Data Integration

Collaborate with data analysts and scientists to integrate and consolidate data from multiple sources

Develop APIs and other interfaces for data access and manipulation

Documentation & Reporting

Document data processes, pipelines, and architectures

Generate reports and visualisations to communicate data insights and pipeline performance

Technical Support

Provide technical support for data-related issues and troubleshoot problems as they arise

Assist in the implementation of data governance and compliance policies

Continuous Improvement

Stay up to date with emerging trends and technologies in data engineering

Participate in code reviews and contribute to the continuous improvement of data engineering practices

What success looks like in the role

Helpdesk tickets are triaged promptly and accurately, and escalated to the right level without unnecessary back-and-forth

Data pipelines run reliably, with data quality issues caught through testing before they reach clients

Data is consolidated cleanly from multiple sources, giving analysts and scientists a dependable foundation to build on

Processes, pipelines, and architectures are well documented, so knowledge is shared rather than held in one head

You grow steadily in confidence across the stack, taking on more complex investigations, bug fixes, and change controls over time

Qualifications & Technical Skills

Proficiency in SQL and experience with relational databases (e.g. MySQL, PostgreSQL)

Experience with data pipeline and workflow management tools (e.g. Apache Airflow)

Familiarity with programming languages such as Python, Java, or Scala

Basic understanding of cloud platforms and services (e.g. AWS, Azure, Google Cloud)

Knowledge of big data technologies (e.g. Spark) is a plus

A bachelor's degree in Computer Science, Engineering, Information Technology, or a related field

Relevant certifications in data engineering or cloud platforms (e.g. AWS, Azure, Google Cloud, Databricks) are a plus