At Aiimi, we’re seeking a Graduate Data Engineer to join our dynamic team and develop their career in data-driven innovation. You will support projects for some of our major clients, helping to improve outcomes for their customer base through reliable, well-structured data solutions. Working closely with Senior Data Engineers, Data Scientists, and client teams, you will support the design, development, and maintenance of data pipelines and infrastructure that enable advanced analytics and AI solutions. This role is ideal for a recent graduate or early-career professional with a strong interest in data engineering, a willingness to learn, and enthusiasm for working in a collaborative, fast-paced consultancy environment. ### Responsibilities - Support the building, maintenance, and optimisation of scalable data pipelines and ETL workflows - Assist with the ingestion, transformation, and integration of structured and unstructured data from multiple sources. - Work with data engineers, data scientists, analysts, and stakeholders to support data availability and quality for modelling and reporting. - Manage and prioritise tasks across projects within a fast-paced consultancy environment, with support from the team. - Write clean, well-documented code for data processing tasks, with opportunities to build confidence through mentoring and code reviews. - Help monitor data pipeline performance and reliability, escalating issues and learning troubleshooting approaches. - Participate in code reviews and team learning activities to develop data engineering standards and best practices. - Support the implementation of data security, privacy, and governance policies while building understanding of best practice. - Assist with the deployment and operationalisation of data solutions in cloud environments. ### Requirements Essential: - A relevant degree, apprenticeship, bootcamp, placement, internship, or personal/project experience in data engineering, computer science, software development, mathematics, analytics, or a related field. - Foundational knowledge of SQL and at least one programming language, such as Python. - Some exposure to data platforms or tools such as Databricks, Spark, or similar technologies through study, projects, or work experience. - Basic understanding of ETL/ELT concepts and how data moves between systems. - Familiarity with relational databases and an interest in learning about modern data storage approaches. - Awareness of cloud platforms such as AWS, Azure, or GCP, and enthusiasm to develop practical experience with cloud data services. - Strong problem-solving skills, curiosity, and the ability to learn quickly with support and guidance. - Good interpersonal skills, with confidence to ask questions, collaborate with others, and comfortable in client-facing environments. Desirable: - Academic, project, or self-led exposure to big data technologies such as Hadoop or Spark. - Awareness of containerisation tools such as Docker or orchestration concepts such as Kubernetes. - An interest in data modelling, data warehousing, and analytics platforms. - Awareness of data security, privacy, and compliance principles. - Relevant coursework, certifications, personal projects, or portfolio work in data engineering, cloud technologies, or software development. ### Benefits - 25 days annual leave (plus bank holidays), increasing by 1 day every two years - Flexible working options – remote/hybrid - Mental health and wellbeing support, including access to counselling - Annual wellbeing allowance (e.g. personal training, fitness, wellness apps) - Up to 10% of your salary in employee benefits, including critical illness cover, life insurance, and private healthcare (post-probation) - Generous company pension contribution - Ongoing professional development and training opportunities