Data Engineer

Final date to receive applications: 22 November 2026 11:59pm

Salary package:

£46,283.00 up to £52,000 per annum in addition to our comprehensive benefits package

The Royal Society of Chemistry (RSC) is seeking an experienced Data Engineer to join our Data team and play a pivotal role in shaping how data is managed, transformed and utilised across the organisation. This is a highly technical, hands‑on role where you'll be responsible for developing and maintaining our data warehouse, building robust data pipelines, and ensuring data from multiple sources is consolidated, standardised and accessible.

Your work will help create a connected view of our customers, products and services, enabling better decision‑making and unlocking the full value of data as a strategic asset. Working at the heart of our data ecosystem, you'll take ownership of the data engineering lifecycle, from data ingestion and transformation through to modelling, quality assurance and delivery. You'll use your expertise in Python, SQL, data warehousing, data modelling and software engineering best practices to design innovative robust, scalable solutions that meet both business and technical needs.

This is an excellent opportunity for someone who enjoys solving complex problems, navigating a varied stakeholder landscape and acting as the bridge between business requirements and technical delivery. You'll have the autonomy to shape solutions, set and embed data architecture standards, champion best practice, and influence how data is managed across the organisation. We're looking for someone who is passionate about data engineering, thrives on continuous learning, and is excited by the opportunity to take ownership, drive improvement and make a lasting impact.

If you're an experienced Data Engineer who enjoys building scalable data solutions with strong grounding in data modelling, working collaboratively with stakeholders, and turning complex challenges into practical outcomes, we'd love to hear from you.

Although this role is contractually based at our Cambridge office, we offer flexible hybrid working. You will have the opportunity to work from anywhere in the UK, with occasional travel to our Cambridge office, typically around once a month or when and if required for a project work. Please be prepared to come to the office more often in your first few months to help you settle in the team.

• Develop effective working relationships with a broad range of stakeholders to identify user requirements, evaluate and deploy data and analytics solutions.
• Analyse and evaluate data from a variety of internal and external data sources, design, test and implement ETL processes.
• Build and maintain data pipelines, orchestrate and schedule ETL from a variety of data sources to a central data repository.
• Transform data, monitor and improve data quality, apply standards and join data to create unified data sets.
• Develop and maintain a joined-up, shared view of customers, products, services, markets and competitors, ensuring this is available to consumers including Business Intelligence tools, CRM/CDP platforms and members of the Data and Analytics function.
• Ensure data is stored securely in a cloud data infrastructure and complies with relevant policies, regulations and legislation.
• Support monitoring and improvements to data quality and data documentation.
• Ensure data assets are documented, data catalogue, lineage and provenance is maintained throughout data architecture.
• Provide guidance, best practice and training to the wider business and end users.
• Work across the organisation, closely with the Data and Analytics team and 3rd parties, delivering data and analytics projects.
• Lead Data Engineering aspects of projects.

• Substantial experience in a full life cycle of date. Including familiarity with data related AWS technologies (e.g. Redshift).
• Strong programming skills and substantial experience designing and building data pipelines (e.g. Python, SQL, Airflow).
• Experience in data standardisation and QA techniques.
• Experience working with data observability tools.
• Experience integrating data with visualisation and business intelligence tools (e.g. Power BI) and creating a single customer view (e.g. consolidating and surfacing CRM/CDP data).
• Experience with version control systems for managing code (e.g. Git).Sorry, the response cut off.}