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Data Engineer

The Role Profile

Location: London Office / Hybrid Working

Reports to: Head of Data Science

Grade: 4

About us

We are Royal College of Pharmacy’s knowledge business. We support health professionals globally make quick and confident decisions about the safe and effective use of medicines to reduce risk and improve patient outcomes.

As a not-for-profit all our resources are invested into creating independent evidence-based content and essential tools that promote best practice in medicines use.

Our experienced editorial team of clinical and scientific writers includes pharmacists and science graduates who triage new information, assess evidence and review changes made by other experts before publication.

Referred to daily by health professionals across healthcare, academic and research settings and relied on by many commercial organisations to operate their businesses, our essential knowledge is available by organisational subscription online through MedicinesComplete and via license.

This is an exciting time to join PhP (Pharmaceutical Press) as we have just become a wholly owned subsidiary of the Royal College. As a wholly owned subsidiary we will have nearly 120 employees and total revenues of more than £18 million. Our surplus is “handed to the Royal College” annually to enable them to fulfil their charitable purposes. For more information visit www.PharmaceuticalPress.com

About this Role:

The Data Engineer will design, build, maintain, and optimise the data platforms, pipelines, and infrastructure that enable PhP to collect, store, process, and analyse data at scale.

The role is responsible for developing and supporting reliable data pipelines that integrate data from a range of source systems, including legacy platforms, into centralised data stores. Working closely with product, engineering, and analytics teams, the Data Engineer will help drive data migration initiatives, ensure the quality and integrity of organisational data, and provide the foundations that enable reporting, analytics, and data-driven decision making across PhP.

Main Accountabilities:

  • Partner with internal stakeholders to understand business challenges and deliver effective, scalable data solutions.

  • Communicate effectively with both technical and non-technical stakeholders, translating complex data concepts into clear business outcomes.

  • Design, develop, test, deploy, and monitor reliable data pipelines and distributed data processing solutions.

  • Develop high-quality, well-documented, and reproducible data models that are scalable, maintainable, and aligned with business needs.

  • Collaborate closely with Data Scientists, Software Engineers, Analysts, and other technology teams to deliver integrated data solutions.

  • Ensure data solutions meet the needs of both data producers and consumers, with a focus on data quality, reliability, governance, and accessibility.

  • Deliver value iteratively through agile ways of working, prioritising outcomes and continuous improvement.

  • Contribute to the evolution of PhP's data platform, engineering standards, and best practices.

  • Maintain awareness of emerging technologies and industry trends, continuously developing technical skills and sharing knowledge across the team.

This list is a summary of the main accountabilities of this role and is not exhaustive. The role holder may be required to undertake other reasonable duties from time to time.

Essential:

We encourage our Data Engineers to continuously learn and adapt to new technologies as project requirements evolve. We are looking for candidates with experience in a number of the following areas:

  • Strong programming skills in Python.

  • Experience designing and building data pipelines, complex ETL processes, and large-scale data migration solutions.

  • Experience with AWS services such as Lambda, DynamoDB, S3, and related cloud-native technologies.

  • Strong communication and stakeholder management skills.

  • Understanding of content modelling, metadata management, taxonomy design, and information architecture principles.

  • Hands-on experience with relational and NoSQL databases.

  • Familiarity with big data concepts and technologies for storing and processing large volumes of data.

  • Practical experience working with a variety of data types, including text, tabular, graph, time-series, geospatial, and image data.

  • Experience with containerisation technologies and public or private cloud environments.

  • Understanding of information security, data governance, and data management best practices.

  • Experience delivering high-quality technical solutions to agreed timescales, ideally within stakeholder-facing or customer-facing environments.

Desirable:

  • Experience designing data architectures within publishing, content, media, or knowledge-focused organisations.

  • Understanding of different data architecture approaches, including Data Lakes, Data Warehouses, Data Mesh, streaming, and batch processing.

  • Experience with emerging AI technologies, standards, and integration patterns, including Model Context Protocol (MCP).

  • Experience contributing to enterprise data modelling, schema design, or content platform modernisation initiatives.

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