Data Engineer

At Aiimi, we're seeking a Data Engineer to join our dynamic team, helping to shape the future of data-driven innovation. You will collaborate with some of our major clients to support projects aimed at enhancing outcomes for their customer base. As a Data Engineer, you will support the design, development, and maintenance of data pipelines and infrastructure that enable advanced analytics and AI solutions. Working closely with Senior Data Engineers, Data Scientists, and client teams, you will contribute to building scalable and reliable data platforms, ensuring data is clean, accessible, and well-structured for analysis. This role is perfect for someone with foundational data engineering skills eager to expand their experience in a collaborative, fast-paced consultancy environment.,

• Assist in building, maintaining, and optimising scalable data pipelines and ETL workflows.
• Support the ingestion, transformation, and integration of structured and unstructured data from multiple sources.
• Collaborate with data scientists, analysts, and stakeholders to ensure data availability and quality for modelling and reporting.
• Manage and prioritise tasks across multiple projects within a fast-paced consultancy environment.
• Write clean, efficient, and well-documented code for data processing tasks.
• Monitor and troubleshoot data pipeline performance and reliability issues.
• Participate in code reviews and contribute to improving data engineering standards and best practices.
• Assist in implementing data security, privacy, and governance policies.
• Support the deployment and operationalisation of data solutions in cloud environments.
  
  1-3 years' experience in data engineering, software development, or related roles.
• Strong proficiency in SQL, with experience in Python or similar programming languages.
• Experience using Databricks to develop and manage data pipelines and workflows.
• Experience working with ETL/ELT tools and data pipeline frameworks (e.g. Apache Airflow, Apache NiFi).
• Familiarity with relational and NoSQL databases.
• Basic understanding of cloud platforms (AWS, Azure, GCP) and their data services.
• Strong problem-solving skills, with the ability to manage priorities across multiple projects.
• Ability to work effectively in a client-facing, consultative environment, confidently engaging with stakeholders to understand requirements and contribute to data-driven solutions.
• Clear communication and documentation skills.
Desirable:
• Exposure to big data technologies (e.g. Hadoop, Spark).
• Knowledge of containerisation and orchestration tools (Docker, Kubernetes).
• Understanding of data modelling and data warehousing concepts.
• Awareness of data security and compliance best practices.
• Relevant certifications or coursework in data engineering or cloud technologies.
  
  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