Senior Data Engineer - UK
Cluepoints
Data Science
United Kingdom
At CluePoints, we’re redefining how clinical trials are run. As the premier provider of Risk-Based Quality Management (RBQM) and Data Quality Oversight software, we harness advanced statistics, artificial intelligence, and machine learning to ensure the quality, accuracy, and integrity of clinical trial data, helping life sciences organizations bring safer, more effective treatments to patients faster.
We’re proud to be an ambitious, fast-growing technology scale-up with a dynamic and diverse international team representing more than 20 nationalities. Collaboration, flexibility, and continuous learning are part of our DNA.
At CluePoints, you’ll find a culture where you can grow, make an impact, and have fun along the way. Guided by our values of Care, Passion, and Smart Disruption, we’re united by a shared mission: to create smarter ways to run efficient clinical trials and deliver AI-powered insights that improve human outcomes worldwide.
This role is ideally on a hybrid basis, in London.
The Role
We’re looking for a Senior Data engineer to join our Finance team to contribute to our mission of transforming clinical research through data-driven insights.
The Senior Data Engineer will play a crucial role within the Data & Analytics team, driving the development and implementation of a centralized Data Warehouse infrastructure. This position involves architecting, designing, and delivering scalable data solutions to streamline and optimize data storage, integration, and management processes. Leveraging expertise in the Kimball Methodology and Azure Data Factory, the Senior Data Engineer will ensure seamless integration of data from diverse sources, maintaining consistency, accuracy, and reliability.
In addition to these responsibilities, the Senior Data Engineer will work closely with Senior Data Analysts to provide well-aggregated and curated datasets, ensuring readiness for reporting and analytics purposes. This collaborative approach is essential to deliver high-quality insights and support data-driven decision-making across the organization.
- Extensive Data Warehouse Experience: At least 7 years of hands-on experience designing, building, and managing data warehouses using the Kimball methodology.
- Proficiency in Azure Tools: Demonstrated expertise in Azure Data Factory (ETL processes), Azure SQL Server, Azure DevOps, Key Vaults, and Logic Apps.
- Strong Data Modelling Skills: Proven ability to design efficient and scalable data warehouse architectures, including the creation of robust staging and production layers.
- Performance Optimization: Experience in optimizing data loads to ensure reliability, scalability, and high performance, with a focus on reducing processing times and improving efficiency.
- Forward-Thinking Vision: A solid understanding of advanced data technologies and practices, with the ability to scale the data warehouse to support future growth and evolving business needs.
- Integration Expertise: Experience integrating data from diverse sources, ensuring data accuracy and consistency throughout the ETL process.
- Problem-Solving Abilities: Adept at troubleshooting and resolving complex data pipeline and infrastructure issues.
- Collaboration Skills: Ability to work closely with data analysts, stakeholders, and cross-functional teams to align data solutions with business objectives.
- Agile and DevOps Practices: Familiarity with CI/CD pipelines and agile workflows to streamline data warehouse development and deployment.
Nice to Have
- Previous SaaS experience - working with Software as a Service (SaaS) companies
- Familiarity with Microsoft Power BI to support data visualization and advanced analytics needs.
- Understanding of cloud cost management strategies to ensure efficient use of Azure resources.
- Proficiency in scripting languages like Python, PowerShell, or Bash for automation and orchestration tasks.
- Hands-on experience with tools and practices to monitor and improve data quality in the pipeline.
- Familiarity with Microsoft Fabric components (such as Fabric Data Factory, Lakehouse, or Warehouse) is advantageous, showing awareness of emerging Microsoft data platform capabilities and how they integrate with existing Azure Data Factory pipelines.
- Experience designing or working with hybrid data architectures (combining data lakes and data warehouses) is a plus, particularly within Azure environments.
Our current data stack includes an enterprise data warehouse built on a Medallion architecture, leveraging the Kimball methodology, and supporting over 70 Power BI models that deliver thousands of insights to stakeholders.
If you're an ambitious and driven professional looking to take your career to the next level, this is the perfect opportunity to join a dynamic and fast-growing company in the exciting e-clinical space. Apply now and help us revolutionize the clinical research industry!
- Lead the design and implementation of robust and scalable data architecture solutions on the Azure platform, ensuring optimal performance and efficiency.
- Drive the implementation of data integration processes to seamlessly ingest data from diverse sources into Azure SQL Server, leveraging Azure Data Factory to design and develop ETL processes efficiently.
- Champion the maintenance of data quality, reliability, and integrity within Azure-stored datasets by enforcing data governance policies, conducting QA checks, and establishing effective monitoring mechanisms to uphold data quality standards.
- Utilize analytical skills to thoroughly review API documentation and analyse raw data and source system data models, ensuring comprehensive understanding and preparation before loading data into the staging area.
- Take ownership of maintaining documentation such as data dictionaries and data models and actively share knowledge and expertise with team members to cultivate a culture of continuous learning and improvement.
- Collaborate with Senior Data Analysts to assist with complex SQL queries and ensure seamless reporting in Power BI. Act as a backup during their absence to maintain reporting continuity and meet requirements.
- Demonstrate adaptability and effectiveness in working under a hybrid working model, delivering high-quality work across global teams with efficiency and professionalism.
- Strong communication and presentation skills to convey technical concepts to non-technical stakeholders and build collaboration across teams.