Alimentiv is a global CRO with a singular focus: advancing therapies for patients with gastrointestinal diseases. GI is our WHY and for more than 30 years that purpose has driven our scientific rigour, operational excellence, and deep therapeutic expertise, including supporting more than 70% of IBD compounds in development.
We operate as a private, profit-with-purpose company, channeling our commercial success back into scientific research, technology, and our people. With approximately 700 people across multiple countries and three service lines, we are growing deliberately, and the capability of our leaders and our organization is central to how we get there.
If you want to do meaningful work, build something real, and invest back in research that changes lives — we want to meet you! Job Overview
We are seeking an experienced Lead Data Engineer to design, develop, and deliver scalable, high-performance data solutions that support enterprise analytics, business intelligence, and AI/ML initiatives.
In this role, you will lead the development of modern data architectures and automated data pipelines using Azure Databricks, Microsoft Fabric, PySpark, SQL, and Azure technologies. You will play a key role in ensuring data quality, governance, and accessibility while enabling advanced analytics and data-driven decision-making.
Working closely with technical teams and business stakeholders, you will provide technical leadership, mentor junior engineers, and drive continuous improvements across the organisation's data ecosystem.
Key Responsibilities
Architect, design, and implement scalable end-to-end data solutions using Azure Databricks, Microsoft Fabric, PySpark, Azure Data Factory, and Azure SQL.
Develop, maintain, and optimise data pipelines supporting data ingestion, transformation, integration, and consumption across enterprise platforms.
Design and implement data models across bronze, silver, and gold layers within modern data lake and warehouse architectures.
Optimise Spark and SQL workloads to improve performance, scalability, reliability, and cost efficiency.
Build API-based integrations, real-time data ingestion frameworks, and reusable pipeline templates to streamline data processing.
Drive automation through Azure DevOps, Git-based CI/CD pipelines, and automated testing frameworks to ensure reliable production deployments.
Prepare and maintain high-quality datasets and analytical models to support business intelligence, reporting, self-service analytics, and AI/ML initiatives.
Ensure compliance with data governance, security, and regulatory requirements, including GxP, GDPR, and HIPAA, where applicable.
Collaborate with business stakeholders, analysts, and IT teams to translate business requirements into effective data engineering solutions.
Provide technical leadership, mentor junior engineers, lead design reviews, and contribute to data architecture roadmaps and continuous improvement initiatives.
Skills & Qualifications Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline; a Master's degree is preferred.
5–8 years of experience designing, developing, and delivering enterprise-scale data solutions, including data warehouses, data lakes, and operational databases.
Expert-level proficiency in Azure Databricks, Microsoft Fabric, PySpark, SQL, and Azure DevOps.
Proven hands-on experience with Azure Data Factory, Azure Data Lake Storage Gen2 (ADLS Gen2), and Azure SQL Server.
Strong understanding of modern data architectures, data modelling, integration, metadata management, data cataloguing, and governance principles.
Experience developing automated data pipelines using REST APIs, JSON, real-time ingestion technologies, and reusable integration frameworks.
Proficiency in CI/CD practices, Git version control, automated testing, and infrastructure-as-code tools such as ARM, Bicep, or Terraform.
Experience with Power BI and developing data models for business intelligence and self-service analytics; knowledge of Tableau or Looker is advantageous.
Understanding of GxP, GDPR, HIPAA, and relevant regulatory requirements; experience within life sciences or healthcare is highly desirable.
Strong communication, stakeholder management, problem-solving, and technical leadership skills, with the ability to work independently, mentor colleagues, and deliver projects within deadlines