At a Glance
- Tasks: Shape data architecture to enhance customer experiences across Springer Nature's research brands.
- Company: Join Springer Nature, a leader in research publishing, committed to innovation and data-driven solutions.
- Benefits: Enjoy flexible working options, professional development opportunities, and a collaborative work culture.
- Why this job: Be part of a transformative journey, influencing data strategies that drive impactful research outcomes.
- Qualifications: Extensive experience in data modelling and governance, with strong communication skills and a collaborative mindset.
- Other info: Opportunity to work with cutting-edge technologies and contribute to a data-driven future.
The predicted salary is between 48000 - 72000 £ per year.
This role will develop a cohesive data architecture in a key area across Springer Nature's research brands, transforming services and products towards a data-driven customer experience.
About you
You bring people together, getting the right artefact in front of the right people to shift the conversation towards agreement and understanding. You learn quickly, taking in the full context and complexity to work out what can and can't be safely set aside for now. You communicate well and ensure stakeholders understand your architectural vision and its relationship to the business capabilities it will enable. You architect with an iterative approach, actively seeking input from multiple points, gathering feedback, and adapting to new requirements and information.
Role Responsibilities
- Collaborate with business stakeholders, technology teams, and data professionals to define and align on a target data architecture that supports strategic goals.
- Drive the development and maintenance of data architecture guidelines and standards to ensure consistency across the organization, including digital products and marketing domains.
- Provide guidance and mentorship to department representatives to promote improved data quality, harmonization, and governance practices.
- Introduce and explain data concepts to senior business and product leaders to foster data literacy and informed decision-making.
- Develop and maintain data models and artifacts to document the as-is and to-be states of the customer data landscape.
- Identify and define desired data products that meet the research organization's needs, ensuring alignment with business requirements.
- Collaborate with teams and solution architects to contribute to the development of the broader data ecosystem, including capabilities like data disambiguation, APIs, and machine learning models.
- Continually validate architecture through delivery with product teams and course correct as necessary.
- Collaborate with data privacy, governance, and management roles to establish and enforce data management, security, and compliance policies within areas of active development, ensuring adherence to relevant regulations (e.g., GDPR).
- Build and maintain strong relationships with key stakeholders, including Solution Architects, Data Governance, Data Directors, Heads of Product, Data Protection Officer (DPO), Enterprise Architects, and Cybersecurity, to ensure the delivery of reliable, right, and secure data solutions.
- Collaborate with other data architects in workshops, planning sessions, and product teams to create shared artifacts, fostering a collaborative and consistent approach to data architecture.
Skills & Experience
Essential
- Extensive experience in data modeling, with a proven track record of successfully modeling complex data domains.
- Demonstrated experience in defining and documenting data strategies, roadmaps, and principles.
- Strong understanding of data governance principles and practices, with experience driving improvements in data quality and harmonization.
- Experience in defining and documenting non-functional requirements (e.g., data management, security, compliance) and ensuring their implementation.
- Ability to review proposed technology options for architectural fit and define appropriate frameworks for technology selection.
- Experience defining success measures and monitoring key data components to ensure performance and reliability.
- Excellent communication and interpersonal skills, with the ability to effectively clarify constraints, trade-offs, and essential decisions to technical and non-technical stakeholders.
- Proven ability to develop strategies to improve data quality and ensure data accuracy and consistency.
- Experience creating regular feedback loops with stakeholders and product teams to ensure alignment and incorporate learnings into the data architecture.
Desirable
- Knowledge of architectural disciplines such as data mesh, business intelligence (BI), data warehousing, and data platforms.
- Experience with cloud-based data solutions and technologies.
- Strong facilitation and alignment skills, with the ability to effectively navigate and influence across organizational silos.
- Experience with aligning Agile delivery teams.
What you will be doing
- 1 month: Collaborate with key stakeholders to understand the research data landscape's current state and identify immediate improvement opportunities. Document the as-is data/technical landscape for research data and the broader domain. Build relationships and feedback loops with data governance, security, and other relevant groups to ensure alignment on data standards, security policies, and architectural principles. Start to map out the existing data sources and identify potential issues that must be addressed.
- 3 months: Maintain a high-level roadmap for the development of the research data ecosystem, outlining key milestones and deliverables for the next 6-12 months, and present to senior leadership. Determine how the technical architecture can support delivery autonomy while supporting consistent user journeys across platforms. Perform feasibility analysis and provide recommendations on build vs. buy for systems supporting agile development, scalability, and data governance. Create an architectural forum to bring together architects and tech leads in research data initiatives.
- 6 months: Refine the roadmap and architecture based on feedback from initial delivery, incorporating lessons learned and adjusting priorities. Scale successful approaches to other areas of the research data ecosystem, empowering teams. Develop and communicate a clear vision for the future of the research data ecosystem, highlighting its role in supporting strategic organizational goals.
Data Architect, SPRINGER NATURE (Basé à London) employer: Golden Bees
Contact Detail:
Golden Bees Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Architect, SPRINGER NATURE (Basé à London)
✨Tip Number 1
Network with professionals in the data architecture field, especially those who have experience in research organisations. Attend industry events or webinars to connect with potential colleagues and learn about their experiences at Springer Nature.
✨Tip Number 2
Familiarise yourself with the latest trends in data governance and architecture, particularly in relation to GDPR compliance. This knowledge will not only enhance your understanding but also demonstrate your commitment to best practices in data management.
✨Tip Number 3
Prepare to discuss your experience with collaborative projects that involved multiple stakeholders. Highlight specific examples where you successfully aligned diverse teams towards a common data architecture goal, as this is crucial for the role.
✨Tip Number 4
Showcase your ability to adapt and iterate on architectural designs based on feedback. Be ready to share instances where you’ve made adjustments to your approach in response to stakeholder input, as this aligns with the iterative nature of the role.
We think you need these skills to ace Data Architect, SPRINGER NATURE (Basé à London)
Some tips for your application 🫡
Understand the Role: Before you start writing your application, make sure you fully understand the responsibilities and requirements of the Data Architect position at Springer Nature. Tailor your application to highlight how your skills and experiences align with their needs.
Highlight Relevant Experience: In your CV and cover letter, focus on your extensive experience in data modelling and governance. Provide specific examples of projects where you've successfully defined data strategies or improved data quality, as these are key aspects of the role.
Showcase Communication Skills: Since the role requires excellent communication and interpersonal skills, include examples that demonstrate your ability to clarify complex concepts to both technical and non-technical stakeholders. This will show that you can effectively bridge gaps between teams.
Emphasise Collaboration: Springer Nature values collaboration with various stakeholders. In your application, mention instances where you've worked with cross-functional teams or led workshops to foster alignment and shared understanding, as this aligns with their collaborative approach.
How to prepare for a job interview at Golden Bees
✨Understand the Data Landscape
Before your interview, make sure you have a solid grasp of the current data landscape at Springer Nature. Familiarise yourself with their research brands and how they utilise data. This will help you articulate how your experience aligns with their needs.
✨Showcase Your Communication Skills
Since the role requires excellent communication with both technical and non-technical stakeholders, prepare examples that demonstrate your ability to clarify complex concepts. Think of times when you successfully bridged gaps between different teams.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Be ready to discuss how you would approach defining data strategies or improving data quality in a collaborative environment.
✨Highlight Your Iterative Approach
The job emphasises an iterative approach to architecture. Be prepared to discuss how you've gathered feedback and adapted your strategies in previous roles. This shows your flexibility and commitment to continuous improvement.