Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and optimize data models, build pipelines, and ensure data quality.
- Company: Join a dynamic team focused on innovative data solutions and analytics.
- Benefits: Enjoy flexible work options, mentorship opportunities, and a collaborative culture.
- Why this job: Make an impact by shaping data architecture and driving insights for the business.
- Qualifications: Strong data modeling experience and proficiency in SQL and BI tools required.
- Other info: Ideal for those passionate about data governance and cross-functional collaboration.
The predicted salary is between 48000 - 72000 £ per year.
What You Will Do
Data Architecture Design & Implementation:
- Develop and optimize Snowflake data models to support analytics and reporting requirements.
- Collaborate with the Data Engineering team to build data pipelines and ETL processes.
- Working with our Head of Data Engineering define the architecture and deployment of reporting solutions with ThoughtSpot, ensuring data is accurate, timely, and easily accessible.
Data Governance & Quality:
- Implement best practices for data governance, including data lineage, metadata management, and data cataloguing.
- Ensure data integrity, consistency, and quality across the organization by working with our Data Quality team to design automated quality checks and monitoring processes.
- Work closely with business stakeholders to understand reporting and analytics needs, translating them into data architecture solutions.
Collaboration with Cross-functional Teams:
- Partner with Data Analysts, Data Engineers, and Product teams to ensure alignment on data structure, reporting requirements, and system integrations.
- Provide technical leadership and mentorship to junior team members.
- Work alongside the business intelligence team to ensure that ThoughtSpot dashboards and reports deliver actionable insights to stakeholders.
Documentation & Best Practices:
- Document data models, architectures, and processes to maintain a knowledge base for the team.
- Establish and enforce best practices for data modeling, security, and scalability.
- Lead the design of the data infrastructure to ensure that it scales with the growing needs of the business.
What We Are Looking For
- Strong experience in data modelling.
- Proficiency in ThoughtSpot or similar business intelligence tools for building interactive dashboards and self-service reporting.
- Strong SQL skills for data querying, optimization, and troubleshooting.
- Experience with data warehouse design principles, dimensional modelling, and cloud data architectures (preferably on AWS, Azure, or GCP).
- Knowledge of Python, Java, or other programming languages for scripting and automation.
- Solid understanding of e-commerce data models, sales funnels, product catalogue management, and customer behaviour analysis.
- Excellent problem-solving skills with a strategic mindset to address data-related challenges.
- Strong communication skills to translate complex technical concepts into understandable language for non-technical stakeholders.
- Ability to work in a collaborative, fast-paced environment with a focus on delivering high-quality results.
- Leadership and mentorship experience in managing or guiding technical teams.
#J-18808-Ljbffr
Data Architect employer: Boden
Contact Detail:
Boden Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Architect
✨Tip Number 1
Familiarize yourself with Snowflake and ThoughtSpot, as these are key tools for the role. Consider taking online courses or tutorials to deepen your understanding of their functionalities and best practices.
✨Tip Number 2
Network with professionals in the data architecture field, especially those who have experience with e-commerce data models. Join relevant online communities or attend meetups to exchange insights and learn from others.
✨Tip Number 3
Prepare to discuss your experience with data governance and quality assurance. Think of specific examples where you implemented best practices or automated processes that improved data integrity.
✨Tip Number 4
Showcase your leadership skills by highlighting any mentoring or team management experiences. Be ready to explain how you guided junior team members and contributed to a collaborative work environment.
We think you need these skills to ace Data Architect
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Data Architect position. Understand the key responsibilities and required skills, such as data modeling, SQL proficiency, and experience with ThoughtSpot.
Tailor Your CV: Customize your CV to highlight relevant experience in data architecture, ETL processes, and collaboration with cross-functional teams. Emphasize your technical skills, especially in SQL and any business intelligence tools you have used.
Craft a Compelling Cover Letter: Write a cover letter that connects your background to the specific requirements of the role. Mention your experience with data governance, quality assurance, and how you've successfully collaborated with stakeholders in the past.
Showcase Your Problem-Solving Skills: In your application, provide examples of how you've tackled data-related challenges in previous roles. Highlight your strategic mindset and ability to communicate complex concepts to non-technical stakeholders.
How to prepare for a job interview at Boden
✨Showcase Your Data Modeling Experience
Be prepared to discuss your previous projects involving data modeling. Highlight specific examples where you developed and optimized data models, particularly in Snowflake or similar environments.
✨Demonstrate Your Technical Skills
Make sure to showcase your proficiency in SQL and any experience with ThoughtSpot or other BI tools. Be ready to explain how you've used these skills to solve real-world problems or improve reporting processes.
✨Emphasize Collaboration and Communication
Since the role involves working with cross-functional teams, share examples of how you've successfully collaborated with Data Analysts, Engineers, and business stakeholders. Highlight your ability to translate technical concepts into layman's terms.
✨Discuss Best Practices and Governance
Talk about your understanding of data governance and quality assurance. Provide insights into how you've implemented best practices for data integrity and consistency in past roles, and be ready to discuss your approach to documentation.
