Data Engineer
Role Overview
The Data Engineer designs, builds, maintains, and optimises data platforms, pipelines, and infrastructure for data collection, storage, processing, and analysis at scale.
The role supports data migration, data quality, reporting, analytics, and evidence-based decision-making across the organisation.
Key Skills for This Role
Full Job Posting
Role overview
The Data Engineer designs, builds, maintains, and optimises data platforms, pipelines, and infrastructure for data collection, storage, processing, and analysis at scale.
The role supports data migration, data quality, reporting, analytics, and evidence-based decision-making across the organisation.
Main responsibilities
- Partner with stakeholders to understand challenges and deliver scalable data solutions; communicate complex concepts as clear business outcomes.
- Design, develop, test, deploy, and monitor reliable pipelines and distributed data processing solutions.
- Build documented, reproducible, scalable data models aligned with business needs.
- Collaborate with data scientists, software engineers, analysts, and technology teams to deliver integrated solutions.
- Support data quality, reliability, governance, and accessibility for producers and consumers.
- Deliver iteratively through agile working, continuous improvement, and outcome-focused prioritisation.
- Contribute to the data platform, engineering standards, and best practices; develop skills and share knowledge.
Essential experience and skills
- Strong Python programming skills and experience building data pipelines, complex ETL, and large-scale data migration solutions.
- Experience with AWS services such as Lambda, DynamoDB, and S3; relational and NoSQL databases; and containerisation and cloud environments.
- Understanding of content modelling, metadata management, taxonomy, information architecture, big data, information security, data governance, and data management.
- Practical experience with varied data types, including text, tabular, graph, time-series, geospatial, and image data.
- Strong communication and stakeholder management; experience delivering quality technical solutions to agreed timescales.
Desirable experience
- Data architecture experience in publishing, content, media, or knowledge-focused organisations is desirable.
- Knowledge of data lakes, data warehouses, data mesh, streaming, and batch processing is desirable.
- Experience with emerging AI technologies, standards, and integration patterns, including Model Context Protocol, is desirable.
- Enterprise data modelling, schema design, or content platform modernisation experience is desirable.
Working arrangement
- Full-time, 35-hour working pattern, with hybrid working.
- Home working is supported, with typically four to eight collaborative face-to-face days per month at the London office.
About Pharmaceutical Press
Pharmaceutical Press is the knowledge business of the Royal College of Pharmacy, providing evidence-based pharmaceutical publications and guidance for healthcare professionals.
Application
- The stated closing date is 15 October 2026; applicants are asked to attach a CV and cover letter.
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