> Markdown version of [/jobs/ext/3325391-data-engineer-ai-innovation](https://www.wearedevelopers.com/jobs/ext/3325391-data-engineer-ai-innovation). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer, AI & Innovation - **Company:** Bloomsbury Publishing Plc - **Location:** London, UK (Remote available) - **Salary:** £65,000.0 - £70,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, BigQuery, Cloud Database, Databases, Data Validation, Information Engineering, Data Infrastructure, Python (Programming Language), Machine Learning, Metadata, Operational Databases, Standard Sql, Search Technologies, Software Construction, Snowflake, Deployment Automation, Data Management, Software Version Control, Data Pipelines, Legacy Systems, Amazon Redshift, Databricks - **Published:** September 9, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5876157600 ## About the Role No specific qualification is required for this role. We are interested in demonstrable skill and judgement however they were acquired. Demonstrable experience building and supporting production data pipelines Strong SQL and Python skills Experience working with cloud-based data warehouses such as BigQuery, Snowflake, Redshift or Databricks Knowledge of modern data orchestration and transformation tools such as Airflow, Dagster or dbt Experience ingesting data from APIs, databases, supplier feeds and other diverse sources Strong data modelling and problem-solving skills with excellent attention to detail Understanding of software engineering best practices including version control and automated deployment Excellent communication skills and confidence working with stakeholders across all levels of the business Experience within publishing, media or content-based industries would be an advantage Knowledge of ONIX, EPUB, semantic search or machine learning data pipelines would be beneficial ## Description Bloomsbury is looking for an experienced and pragmatic Data Engineer to join our AI & Innovation team. It's an exciting opportunity to help shape Bloomsbury's data infrastructure and support some of the company's most ambitious AI and commercial initiatives. As the first dedicated Data Engineer in the business, you will be responsible for building and maintaining the data platforms, pipelines and governance frameworks that underpin insights, forecasting, discovery, licensing and other strategic projects. You will work closely with Data Scientists, Technology, Legal and colleagues across our publishing divisions, helping to ensure trusted, well-modelled data is accessible throughout the organisation. This is a foundational role rather than a maintenance one, and suits someone who would rather build infrastructure that lasts than run someone else's. The ideal candidate will enjoy building reliable systems from the ground up, have a strong understanding of modern data engineering practices, and be comfortable collaborating with both technical and non-technical stakeholders. The role will ingest data from multiple systems into GCP (BigQuery) you will be comfortable working with varying data sources and types. As a small engineering team, we value adaptability, we will have requests from various parts of the business that require learning tools, implementing code, and working in areas you're unfamiliar with. Problem solving is key. The role Design, build and maintain Bloomsbury's Single Source of Truth, ensuring colleagues work from trusted and well-documented datasets Lead the migration and consolidation of data into BigQuery and support the retirement of legacy systems Develop and manage production data pipelines that ingest information from internal systems, third-party providers and supplier platforms Implement data quality checks, monitoring, testing and lineage processes to ensure data accuracy and reliability Provide the data foundations required for AI initiatives, including forecasting models, semantic search and licensing solutions Model, reconcile and standardise publishing data including metadata, sales, stock and rights information Collaborate with Data Scientists to move analytical models from proof-of-concept into dependable production environments Apply governance, security and access controls in partnership with Technology and Legal teams Document systems, processes and pipelines to ensure knowledge is shared and solutions remain maintainable