At a Glance
- Tasks: Design and deliver advanced data solutions using modern technologies like Snowflake and AWS.
- Company: Join a high-performing data team in a dynamic London-based organisation.
- Benefits: Competitive day rate, hybrid work model, and opportunities for professional growth.
- Why this job: Shape scalable data architectures and make a real impact on business strategies.
- Qualifications: Experience as a Data Architect with strong skills in data modelling and cloud platforms.
- Other info: Collaborative environment with mentorship opportunities and cutting-edge technology.
The predicted salary is between 54000 - 84000 £ per year.
Location: London (Hybrid - minimum 2 days per week in the office)
Day Rate: Market rate (Inside IR35)
Contract Duration: 6 months
Role Overview
We are seeking an experienced Data Architect to work with a high-performing data team, designing and delivering advanced data solutions that support the future data strategy of the organisation. You will harness modern technologies including Data Vault, Snowflake, DBT, Airflow and AWS/Azure to shape scalable, future-proof data architectures.
In this role, you will be responsible for defining, owning and governing data models across delivery teams, ensuring alignment with enterprise architecture principles and business objectives. You will collaborate closely with engineers, product managers, data scientists and the wider architecture community to design innovative, high-value data products and services.
Key Responsibilities
- Triage new data requirements, assess their architectural impact and provide estimates for changes to data models.
- Design, develop and enhance business and physical data models to meet evolving analytical and reporting needs.
- Act as the custodian of data models, defining modelling standards and ensuring consistent adoption across delivery teams.
- Create data architecture solutions that meet business needs and align with target-state architecture.
- Document, communicate and centrally manage data models and associated artefacts.
- Collaborate with the wider architecture community to promote alignment, reuse and innovation.
- Apply strong expertise in data warehousing and end-to-end analytics architecture to bring structure and clarity to reporting environments.
- Design and implement data models using methodologies such as 3NF, Dimensional and Data Vault.
- Stay up to date with industry advancements, including machine learning and modern algorithmic techniques at scale, and embed best practice into data design.
- Influence engineering and product teams to adopt robust data modelling and architecture standards.
- Develop a deep understanding of business processes and the data they generate, identifying opportunities to structure and use data to drive business value.
- Provide technical leadership and mentorship to data engineers.
- Partner with data scientists to productionise research models on Snowflake and AWS.
- Engage with product and business stakeholders to align data and AI solutions with enterprise strategy.
Essential Skills and Experience
- Strong experience as a Data Architect or senior Data Modeller within complex data and analytics environments.
- Deep expertise in data warehousing and end-to-end analytics architecture.
- Proven experience with data modelling methodologies including 3NF, Dimensional and Data Vault.
- Strong understanding of modern data platforms and cloud-based architectures.
- Experience designing data solutions that incorporate machine learning or advanced analytics use cases.
- Excellent communication and influencing skills, with the ability to engage both technical and non-technical stakeholders.
- Strong stakeholder management and cross-functional collaboration skills.
- Highly analytical mindset with the ability to translate business requirements into effective data architecture solutions.
- Experience working with or supporting cloud migrations.
Languages: Python (primary), SQL, Bash
Cloud: Azure, AWS
Tools: Airflow, DBT, Docker, Fargate, FastAPI
Data Platforms: Snowflake, Delta Lake, Redis, Azure Data Lake
Infrastructure and Operations: Terraform, GitHub Actions, Azure DevOps, Grafana, Azure Monitor
Desirable Skills and Experience
- Experience working with enterprise data platforms such as Snowflake and Azure Data Lake.
- Experience deploying data or machine learning models as APIs using FastAPI or Azure Functions.
- Understanding of monitoring, model performance tracking and observability best practices.
- Familiarity with orchestration tools such as Airflow or Azure Data Factory.
Data Architect employer: Stott & May Professional Search Limited
Contact Detail:
Stott & May Professional Search Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Architect
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the data space. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on a Data Architect role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data architecture projects. Whether it's a cool data model you designed or a successful cloud migration, having tangible examples can really set you apart when chatting with potential employers.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each opportunity. Research the company’s data strategy and mention how your experience with Snowflake or Data Vault aligns with their needs. This shows you’re genuinely interested and not just sending out generic applications.
✨Tip Number 4
Use our website to apply! We’ve got loads of resources to help you land that Data Architect gig. Plus, applying through us means you’ll be part of a community that values innovation and collaboration in data solutions. Let’s get you that job!
We think you need these skills to ace Data Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Architect role. Highlight your experience with data modelling methodologies like 3NF, Dimensional, and Data Vault, and showcase your expertise in cloud platforms like AWS and Azure.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for our team. Mention specific projects where you've designed data solutions or collaborated with cross-functional teams.
Showcase Your Technical Skills: Don’t forget to list your technical skills clearly. We want to see your proficiency in Python, SQL, and tools like Airflow and DBT. Make it easy for us to see how you can contribute to our data architecture!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at Stott & May Professional Search Limited
✨Know Your Data Architecture Inside Out
Make sure you’re well-versed in data modelling methodologies like 3NF, Dimensional, and Data Vault. Brush up on your experience with tools like Snowflake and AWS/Azure, as well as your understanding of cloud-based architectures. Being able to discuss these topics confidently will show that you’re the right fit for the role.
✨Showcase Your Collaboration Skills
Since this role involves working closely with engineers, product managers, and data scientists, be prepared to share examples of how you've successfully collaborated in the past. Highlight your communication skills and how you’ve influenced teams to adopt best practices in data architecture.
✨Prepare for Technical Questions
Expect to face technical questions that assess your problem-solving abilities and architectural impact assessments. Practice explaining your thought process when designing data solutions and how you would approach new data requirements. This will demonstrate your analytical mindset and ability to translate business needs into effective data architecture.
✨Stay Updated on Industry Trends
Familiarise yourself with the latest advancements in machine learning and modern algorithmic techniques. Be ready to discuss how you can embed these best practices into data design. Showing that you’re proactive about staying current will impress interviewers and highlight your commitment to innovation.