Senior Data Engineer

Sector Data Science Role Senior Executive Contract Type Permanent Hours Full Time

Job Title: Senior Data Engineer (Fixed-Term Contract)
Location(s): Berlin, Germany and London, England
Final date to receive applications
: 23/10/2026
About Springer Nature Springer Nature opens the doors to discovery for researchers, educators, clinicians and other professionals. Every day, around the globe, our imprints, books, journals, platforms and technology solutions reach millions of people. For over 175 years our brands and imprints have been a trusted source of knowledge to these communities and today, more than ever, we see it as our responsibility to ensure that fundamental knowledge can be found, verified, understood and used by our communities - enabling them to improve outcomes, make progress, and benefit the generations that follow.
About the Us SN Data's mandate is to define a holistic data strategy for all of Springer Nature. Bringing cross-department alignment, providing direction and enabling prioritisation with a view to amplify the impact that data has on our business. Our aim is to help data producers and consumers create new opportunities and find better ways of working, by putting data to work with best practices, and giving people easy access to data they can trust.
About the Role As a Senior Data Engineer in SN Data, you will be joining a new programme of work to transform how Springer Nature uses its data: building up data capabilities, creating a data platform and engineering capability (technology, people and process) to create a foundation for the future, adding value to cross-organisation Initiatives and kick-starting data-driven Innovation.
Across the programme, our teams are cross-functional, diverse and made up of different experience levels. All team members collaborate to deliver the best solutions that satisfy our customers' needs.
Role Responsibilities:

• Design, build, and maintain scalable data pipelines in Google Cloud and Big Query to support analytics, reporting, and AI/ML use cases.

• Collaborate with data analysts, BI developers, architects, and data governance teams to deliver reliable and user-focused data solutions.

• Identify, onboard, and integrate new data sources while assessing data quality, completeness, bias, and business value.

• Develop and optimise data models, transformations, and workflows that enable efficient and repeatable data processing.

• Monitor data pipelines and services, troubleshoot production issues, and implement proactive alerting and data quality controls.

• Ensure data is managed securely and in compliance with GDPR, governance standards, and data security best practices.

• Drive process improvements and self-service capabilities that enable data owners and business users to access and leverage data effectively.

• Mentor junior engineers, promote engineering best practices, and contribute to the wider data engineering community through knowledge sharing and technical leadership.

• Strong SQL skills and proven experience building and supporting data solutions on cloud platforms such as GCP, AWS, or Azure using technologies such as Python, Java, Scala, and DBT.

• Experience designing, developing, and optimising production-grade data pipelines and data products, from source systems through to end-user consumption.

• Strong understanding of data engineering best practices, including data quality, observability, monitoring, security, governance, and cost optimisation.

• Experience working in Agile, cross-functional teams with collective code ownership, CI/CD practices, test automation, and production support responsibilities.