Senior Business Intelligence Data Engineer

About us
We are Digital Science and we are advancing the research ecosystem.

Department: Chief of Staff
Location: UK (home based)

Description
We are a pioneering technology company, and our vision is of a future where a trusted and collaborative research ecosystem drives progress for all. We believe in better, open, collaborative and inclusive research. In creating the next generation of tools and working in partnership with the community we tackle some of the biggest challenges to research. In order to achieve our vision, we need innovative, inspiring and dynamic people to join our team. Want to join us?

Your new role
The I&A function works with a centralised data warehouse built in Google BigQuery, which serves as the single source of truth for business data across the organisation. The warehouse breaks down data silos within Digital Science, enables the development of automated, contextualised reports as well as ad hoc analyses, supporting improved data accessibility and the communication of insights across the business.

Key responsibilities
The Data Engineer role is essential for building and maintaining robust data pipelines between source enterprise business systems and BigQuery, and data modelling. This includes designing and managing data transformation processes within BigQuery to clean, join, and aggregate data into report- and analysis-ready datasets. Additionally, the Data Engineer will develop a deep understanding of the data models within our core enterprise systems, providing critical support for change management, system modifications, and integrations to ensure seamless data operations.

Please note – due to business need, we can only accept applications from candidates who reside in the UK where we have an established legal entity. If you apply from outside of this area, your application will not be considered. We may close this position early if we receive a high volume of applications.

What You’ll Be Doing

• Collaborate with cross-functional teams to identify, collect, and validate data sources and analytics requirements.
• Design, develop, implement and maintain data systems and ETL/ELT processes that support data processing, data integration, and data transformation. This includes setting up and managing Digital Science’s Fivetran instance, as well as developing and maintaining codebases in cloud functions/GBQ pipelines for API calls to non‑Fivetran supported data sources.
• Develop and maintain data transformation and modelling processes using Dataform or dbt.
• Implement and maintain best practices for data governance, data security, and data quality, alerting systems and CI/CD processes.
• Play a central role in business system procurement and change management processes, to advise on the downstream impact for reporting and analytics of system modification, integration and implementation.
• Stay current with industry trends and technologies to identify opportunities for innovation and improvement.

What You’ll Bring To The Role

Essential Experience & Skills:

• Experience as a Data Engineer or similar role working within a modern, cloud‑based environment.
• Strong SQL development skills, including experience designing modular, maintainable data models and transformations.
• Practical experience with SQL-based transformation frameworks such as Dataform or dbt, including managing pipelines as code and version control.
• Understanding of DevOps practices (CI/CD, Git workflows, environment management).
• Hands‑on experience with cloud data warehouses, preferably Google BigQuery, including performance optimisation, cost management and working with large datasets.
• Experience developing and maintaining ELT/ETL pipelines with tools such as Fivetran, Stitch, Airbyte or similar.
• Good understanding of data modelling principles (e.g., dimensional modelling) and best practices for data quality, lineage tracking and governance.
• Ability to design robust, testable, and scalable data products and processes, with attention to reliability, documentation and long-term maintenance.
• Excellent communication skills, enabling effective collaboration with technical and non‑technical stakeholders.

Desirable Experience

• Exposure to Google Cloud Platform (GCP) services beyond BigQuery, such as Cloud Functions, Cloud Storage, Pub/Sub or Cloud Run.
• Experience with data quality frameworks and automated monitoring, including alerting, anomaly detection, or testing frameworks.
• Familiarity with data visualisation and BI tools, such as Looker, Looker Studio, Tableau or Power BI.
• Knowledge of AI/machine learning concepts, and experience using tools such as Vertex AI, BigQuery ML or similar.

Don’t worry if you don’t meet every qualification—let us be the judge! Studies show that many qualified candidates from under-represented groups hesitate to apply unless they meet every single requirement. We are dedicated to building a diverse and inclusive team and strongly encourage you to submit your application.

Living our Values
We invest in, nurture and support innovative businesses and technologies that make all parts of the research process more open, efficient and effective.

Our vision
At Digital Science, our vision is to see research flow seamlessly – trusted, collaborative, and accessible – fueling breakthroughs that push humanity forward.

Equal opportunity
As an equal opportunity employer, we are committed to building and nurturing a workplace where every individual feels valued and belongs. All applicants will be considered for employment without attention to race, colour, religion, age, sex, sexual orientation, gender identity, national origin, veteran, or disability status.