At a Glance
- Tasks: Lead data engineering and architecture for innovative research data products.
- Company: Join a leading global publisher with a focus on collaboration and innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with a strong emphasis on knowledge sharing and collaboration.
- Why this job: Shape the future of research data and make a real impact in the academic world.
- Qualifications: Experience in data architecture and a passion for solving complex problems.
The predicted salary is between 60000 - 80000 £ per year.
The role is to provide data engineering and architectural leadership to teams building core data products and services powering Springer Nature’s researcher brands.
About you
You’re happy working across teams and departments to align and coordinate the development and delivery of data‑centric solutions. You spot risks and opportunities and fill in the gaps between delivery teams. You help remove blockers throughout the data supply chain. You produce demos and MVPs for analysis and to test out possible solutions that you can use to demonstrate ideas or gaps. You take an iterative approach to solving complex problems and seek feedback to quickly arrive at the best result.
Role Responsibilities
- Coordinate across teams to ensure consistent data product development and utilisation, establishing and delivering the defined data architecture. This includes working with the Data Architect to understand team needs, use cases, and constraints for the use case data ecosystems.
- Work with both data producers and consumers to optimise existing data products and the data within them to meet evolving business needs.
- Advocate for teams delivering data‑as‑a‑product.
- Collaborate on the design of the research data ecosystem, addressing disambiguation, data product creation, API development, model building, harmonisation, standardisation, and governance.
- Adopt company‑standardised technology, including cloud platforms, and collaborate with technology teams to improve offerings.
- Consider the best technology for data teams, given a spectrum of technical literacy.
- Work with data privacy and governance teams to ensure data security and appropriate accessibility, adhering to relevant regulations (e.g., GDPR).
- Build relationships with other departments/disciplines/groups to ensure alignment and collaboration.
- Clarify constraints, trade‑offs, or important decisions to non‑technical stakeholders.
- Introduce business and product leaders to data and data engineering concepts and align solutions to user and business needs.
- Foster a safe and collaborative technical community, growing technical knowledge and cultivating knowledge sharing in and across teams.
- Provide data‑related technical and architectural assistance to product delivery teams and IT when needed.
- Assist and support tech leads and senior developers to help unblock issues.
Skills & Experience
Essential
- Proven experience designing, delivering, and scaling data‑intensive applications.
- Demonstrated ability to architect data solutions that meet performance, scalability, and security requirements.
- Experience working on transformation projects involving introducing new technologies and ways of working within a business.
- Ability to drive adoption of new data architectures and technologies.
- Ability to clarify and uncover technical requirements, risks, and opportunities with tech leads and collaborators.
- Experience translating business needs into technical specifications.
- Where necessary, advocate for and enforce cross‑functional technical and data requirements (e.g., GDPR, security, operability, etc.).
- Deep, demonstratable experience delivering with various types of databases and design, including relational databases, NoSQL databases, graph databases, vector stores, and data warehouses, particularly in cloud environments.
- Experience with data modelling techniques and data warehousing methodologies (e.g., Kimball, Inmon, Data Vault).
- Hands‑on experience with cloud data platforms and services (e.g., AWS, Azure, GCP).
- Familiarity with cloud‑native data architectures and technologies.
Desirable
- Experience with data management tools and processes.
- Experience with AI and Machine Learning, including MLOps practices.
- Experience with decentralised Data Mesh and Data Product architecture principles.
What you will be doing
1 month
- Collaborate with key stakeholders (product managers, engineers, architects) to understand the current state of the research data landscape and identify immediate opportunities for improvement.
- Document the as‑is data/technical landscape for research data and the wider domain.
- Begin building 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 need to 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 our platforms.
- Perform feasibility analysis and provide recommendations on Build versus Buy for systems that support the agile development process, scalability, and data governance requirements.
- Create an architectural forum to bring together architects and tech leads in the research data initiatives.
6 months
- Based on feedback from initial delivery, refine the roadmap and architecture, incorporating lessons learned and adjusting priorities as needed.
- Scale the 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 organisational goals.
Having a good command of English is important; collaboration is important in our day‑to‑day work, so being able to communicate your ideas and understand others is key.
For all roles in all locations, we offer a competitive, industry‑benchmarked salary.
Data Solution Architect employer: Dormont Manufacturing Co
Springer Nature is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Data Solution Architect role. With a strong emphasis on employee growth, you will have the opportunity to lead transformative data projects while working alongside talented professionals in a supportive environment. The company offers competitive salaries and benefits, along with a commitment to professional development, making it an ideal place for those seeking meaningful and rewarding employment in the heart of the research data landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Data Solution Architect
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the data game. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your best work, especially those data solutions you've architected. Demos and MVPs are great to showcase your problem-solving approach. Make sure to share this during interviews to give them a taste of what you can do.
✨Tip Number 3
Be proactive! Don’t just wait for job postings to pop up. Reach out directly to companies you admire, like us at StudySmarter. Express your interest and ask about potential opportunities. Sometimes, the best roles aren’t even advertised!
✨Tip Number 4
Prepare for those interviews! Research common questions for Data Solution Architects and practice your responses. Be ready to discuss how you’ve tackled complex problems and collaborated across teams. And remember, we love seeing candidates who can communicate technical concepts clearly to non-techies!
We think you need these skills to ace Data Solution Architect
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with data solutions and architecture. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Showcase Your Collaboration Skills:Since this role involves working across teams, it’s essential to demonstrate your ability to collaborate effectively. Share examples of how you've worked with different departments to deliver data-centric solutions.
Highlight Technical Expertise:We’re looking for someone with a solid grasp of various databases and cloud platforms. Be sure to mention any hands-on experience you have with technologies like AWS, Azure, or GCP, as well as your familiarity with data modelling techniques.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Dormont Manufacturing Co
✨Know Your Data Architecture
Make sure you understand the key principles of data architecture and how they apply to the role. Brush up on your knowledge of cloud platforms like AWS, Azure, or GCP, and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Collaboration Skills
Since this role involves working across teams, prepare examples that highlight your ability to collaborate effectively. Think about times when you’ve coordinated with product managers, engineers, or other stakeholders to deliver data solutions.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during the interview. Be ready to explain your experience with various databases, data modelling techniques, and how you've tackled challenges related to data governance and security.
✨Demonstrate Your Problem-Solving Approach
The role requires an iterative approach to solving complex problems. Prepare to discuss specific examples where you identified risks and opportunities, and how you used feedback to refine your solutions. This will show your adaptability and commitment to continuous improvement.
