Senior Data Engineer

Due to continued growth, we are looking for a Senior Data Engineer to join our Professional Services division. This is a key technical leadership role within a cross-functional Data Consulting team spanning data engineering, data science, AI, analytics, and visualisation.

You will partner with clients across multiple industries, shaping solutions that use modern data architectures, AI techniques, and advanced analytics to unlock measurable value from their data assets.

A day in the life of an Aiimi Senior Data Engineer:

• Leading the design and delivery of scalable, secure, and high-performance data platforms across structured, semi-structured, and unstructured sources.
• Acting as a technical authority for data engineering best practices, data architecture, and AI model integration into production systems.
• Guiding and mentoring junior engineers, reviewing code, and championing engineering excellence.
• Working with stakeholders to identify opportunities for AI and machine learning, and ensuring data pipelines are built to support those needs.
• Capturing and translating complex business requirements into robust technical specifications.
• Designing and implementing new data ingestion, transformation, and storage processes that maximise performance and quality.
• Building and orchestrating highly optimised, cloud-native data and AI pipelines.
• Leading root cause analysis of data quality issues, implementing preventative measures, and advising on data governance.
• Defining security models, access controls, and compliance measures for sensitive data.
• Partnering with data scientists to streamline the deployment of machine learning models into production environments.
• Driving the adoption of automation, DevOps, and MLOps practices in the data environment.
• Ensuring solutions are deployed to centralised, self-service platforms for broad organisational benefit.

Requirements:

• Leadership: proven experience guiding engineering teams, influencing stakeholders, and setting technical direction.
• Collaboration: ability to work closely with subject matter experts, AI specialists, and cross-functional teams.
• Communication: skilled at translating complex architectural and AI concepts to both technical and business audiences.
• Problem Solving: leveraging data and AI to solve high-impact business problems.
• Analytical Thinking: designing solutions that are both technically elegant and pragmatically achievable.
• Quality Focus: delivering robust, maintainable, and well-documented solutions.
• Innovation Mindset: continually exploring new technologies, AI capabilities, and design patterns.

Technologies / Tools:

• Expert-level SQL and Python skills.
• Proven experience with Azure (ADF, Azure Databricks, Data Lake Storage, SQL DWH) or other cloud platforms.
• Deep understanding of distributed processing (Spark, Databricks, etc.).
• Experience designing data architectures for structured, semi-structured, and unstructured data.
• Familiarity with machine learning frameworks and operationalisation of AI models.
• Knowledge of MLOps tooling and lifecycle management.
• Strong grasp of CI/CD pipelines, containerisation (Docker, Kubernetes), and automation tools.

Benefits:

• 25 Days holiday (excluding bank holidays) – increasing by a day every 2 years.
• Flexible working options – 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.