About this role
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 ticketsEscalate issues to the correct level of supportMonitor the helpdesk queue and follow up on outstanding tickets and defectsBuild exposure to client solution queries and investigations, bug fixes, and change controls Data Pipeline Development
Assist in designing, building, and maintaining scalable data pipelinesImplement ETL (Extract, Transform, Load) processes to ingest data from various sourcesEnsure 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 sourcesDevelop APIs and other interfaces for data access and manipulation Documentation & Reporting
Document data processes, pipelines, and architecturesGenerate reports and visualisations to communicate data insights and pipeline performance Technical Support
Provide technical support for data-related issues and troubleshoot problems as they ariseAssist in the implementation of data governance and compliance policies Continuous Improvement
Stay up to date with emerging trends and technologies in data engineeringParticipate 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-forthData pipelines run reliably, with data quality issues caught through testing before they reach clientsData is consolidated cleanly from multiple sources, giving analysts and scientists a dependable foundation to build onProcesses, pipelines, and architectures are well documented, so knowledge is shared rather than held in one headYou 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 ScalaBasic understanding of cloud platforms and services (e.g. AWS, Azure, Google Cloud)Knowledge of big data technologies (e.g. Spark) is a plusA bachelor's degree in Computer Science, Engineering, Information Technology, or a related fieldRelevant certifications in data engineering or cloud platforms (e.g. AWS, Azure, Google Cloud, Databricks) are a plus