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For Companies At a Glance
- Tasks: Design and build robust data pipelines to transform messy data into clean assets.
- Company: Creative Tech Platform focused on innovative data solutions.
- Benefits: Competitive salary, autonomy in your role, and opportunities for growth.
- Why this job: Tackle real-world data challenges and shape the future of our platform.
- Qualifications: Expertise in Python, Azure Data Lake, and hands-on experience with messy data.
- Other info: Join a dynamic team where your contributions make a real impact.
The predicted salary is between 54000 - 90000 ÂŁ per year.
A Creative Tech Platform is looking for a Data Architect to take ownership of the end-to-end data supply chain that underpins their platform. This is a hands-on, technical role for someone who thrives in messy, real-world data environments and enjoys building robust systems from the ground up. You’ll play a critical role in transforming inconsistent, legacy data into clean, structured, and future-ready assets — laying the foundations for a scalable in-house platform.
What You’ll Be Doing
- At the core of this role is designing and owning the “dirty-to-clean” data journey:
- Build the Dirty-to-Clean Pipeline: Design and write Python/ETL pipelines to ingest messy, non-standard data dumps (CSV, XML, JSON) from diverse legacy museum systems.
- Unstructured Data Processing: Implement pipelines to handle high-volume media assets, including image validation, thumbnail generation, and technical metadata extraction.
- Data Quality Automation: Create automated “gatekeepers” that validate and reject non-compliant data before it reaches the platform.
- Infrastructure as Code: Deploy and manage your own data infrastructure using Terraform, owning it end to end.
- Future-Proofing the Platform: Design the data schema and lineage (provenance) architecture that will underpin the next generation of our in-house platform.
Must-Have Skills
- Python Expert: You build robust, testable data applications — not just scripts. Strong experience with Pandas, Pydantic, and FastAPI.
- Deep hands-on experience with Azure Data Lake Gen2, Azure Functions (serverless), and CosmosDB / NoSQL.
- Code-First Mindset: Comfortable working without a dedicated DevOps team. You write and maintain your own Terraform and CI/CD pipelines.
- Messy Data Experience: You’ve dealt with real-world data problems: deduplication, charset issues, schema mismatches, and inconsistent source systems — and have the scars to prove it.
Nice to Have
- Experience working with vector databases (e.g. for AI-powered search).
- Understanding of data provenance and lineage, including tracking data usage and transformations over time.
Why This Role?
- High ownership and autonomy — you design and build the data foundation.
- Technically challenging problems with real-world impact.
- Opportunity to shape the future architecture of a growing platform.
- Work at the intersection of data engineering, infrastructure, and long-term platform design.
Data Architect in London employer: Source
Contact Detail:
Source Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Architect in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving messy data transformations or Python pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and real-world data challenges. Be ready to discuss how you've tackled messy data issues and built robust systems. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Data Architect in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Data Architect role. Highlight your experience with Python, ETL pipelines, and any messy data challenges you've tackled. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for transforming messy data into clean assets and how you’ve done it in the past. Let us know why you're excited about this role and our Creative Tech Platform.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work with Azure Data Lake, Terraform, or any other tech mentioned in the job description. We love seeing real-world applications of your skills.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Source
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of data you'll be working with. Brush up on your experience with messy data, and be ready to discuss specific challenges you've faced, like deduplication or schema mismatches. This will show that you can handle the real-world data problems that come with the role.
✨Showcase Your Technical Skills
Prepare to demonstrate your Python expertise and familiarity with tools like Pandas and FastAPI. Bring examples of your previous work, especially any robust data applications you've built. If you’ve got experience with Azure Data Lake or Terraform, make sure to highlight that too!
✨Discuss Your Problem-Solving Approach
Be ready to talk about how you tackle data quality issues and automate processes. Share specific examples of how you've implemented data validation or created automated gatekeepers in past projects. This will illustrate your hands-on experience and code-first mindset.
✨Understand the Bigger Picture
Research the company’s platform and think about how your role as a Data Architect fits into their vision. Be prepared to discuss how you would design the data schema and lineage architecture for future-proofing their platform. Showing that you understand the long-term impact of your work will set you apart.
