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For Companies At a Glance
- Tasks: Design and implement cloud-based data solutions for analytics and business intelligence.
- Company: Join a dynamic team focused on innovative data architecture and solutions.
- Benefits: Enjoy flexible work options, competitive pay, and opportunities for professional growth.
- Why this job: Be part of a collaborative culture that values data-driven decisions and innovation.
- Qualifications: Experience with AWS services and strong skills in data modelling and ETL/ELT processes required.
- Other info: Ideal for tech-savvy individuals passionate about data and cloud technologies.
The predicted salary is between 48000 - 84000 £ per year.
We are looking for a skilled Data Architect to join our team. This role involves designing and implementing data solutions on the cloud, including data lakes, warehouses, and pipelines. You’ll collaborate with teams to ensure data is accessible, optimized, and secure for analytics and business intelligence.
Key Responsibilities:
- Architect scalable, secure cloud-based data systems using AWS services like Redshift, S3, Glue, and DynamoDB to support analytics and machine learning.
- Develop and manage ETL/ELT workflows, transforming and processing data using AWS Glue, Apache Spark, and custom Python solutions.
- Create and maintain relational and NoSQL data models to ensure efficient querying, storage, and reporting.
- Integrate and consolidate data from diverse sources to ensure accuracy and consistency for analytics.
- Implement data governance and security practices, including encryption, IAM roles, and compliance with GDPR and SOC 2.
- Continuously optimize data systems for performance, cost efficiency, and scalability, ensuring high availability and reliability.
- Partner with data engineers, data scientists, and business analysts to design solutions that meet business needs and enable data-driven decisions.
- Maintain documentation on architecture, workflows, and best practices to ensure consistency and operational continuity.
Required Skills & Experience:
- Extensive experience with AWS services like Redshift, S3, Glue, RDS, and DynamoDB for building data architectures.
- Strong background in designing and automating ETL/ELT pipelines using AWS Glue, Spark, and Python.
- Expertise in data modeling, structuring relational and NoSQL data for optimal performance.
- Familiarity with data governance, encryption, IAM, and regulatory compliance (e.g., GDPR, SOC 2).
- Experience with frameworks like Hadoop, Spark, or Kafka for processing large datasets.
- Proficiency in Python, SQL, and Java for developing custom data workflows and querying large datasets.
- Knowledge of infrastructure management tools such as CloudFormation, Terraform, or AWS CDK.
- Ability to work across teams (data engineers, analysts, business stakeholders) to deliver data solutions that meet business needs.
Preferred Qualifications:
- AWS Certified Solutions Architect – Associate, AWS Certified Big Data – Specialty, or similar certifications.
- Experience with AWS Kinesis, Kafka, or other real-time data streaming technologies.
- Familiarity with tools like Apache Atlas or AWS Glue Data Catalog.
- Experience integrating data systems with machine learning workflows.
- Experience with services like Amazon EMR, Redshift Spectrum, and AWS Data Pipeline.
If you’re an experienced Data Architect with a strong background in AWS and data solutions, we’d love to hear from you!
Data Architect employer: Cloud Bridge
Contact Detail:
Cloud Bridge Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Architect
✨Tip Number 1
Familiarise yourself with AWS services, especially Redshift, S3, and Glue. Understanding these tools inside out will not only help you in interviews but also demonstrate your commitment to the role.
✨Tip Number 2
Network with current or former employees at StudySmarter on platforms like LinkedIn. Engaging with them can provide insights into the company culture and the specific challenges they face, which you can address in conversations.
✨Tip Number 3
Prepare to discuss real-world examples of your experience with ETL/ELT workflows and data modelling. Being able to articulate your past projects will showcase your expertise and problem-solving skills.
✨Tip Number 4
Stay updated on the latest trends in data architecture and cloud technologies. Showing that you're proactive about learning can set you apart from other candidates and demonstrate your passion for the field.
We think you need these skills to ace Data Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS services, ETL/ELT pipelines, and data modelling. Use specific examples that demonstrate your skills in designing cloud-based data systems.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about data architecture and how your background aligns with the responsibilities outlined in the job description. Mention any relevant certifications or projects.
Showcase Relevant Projects: If you have worked on projects involving AWS, data lakes, or machine learning, include these in your application. Describe your role and the impact of your contributions to highlight your expertise.
Highlight Collaboration Skills: Since the role involves working with various teams, emphasise your ability to collaborate effectively. Provide examples of how you've partnered with data engineers, analysts, or business stakeholders in past roles.
How to prepare for a job interview at Cloud Bridge
✨Showcase Your AWS Expertise
Make sure to highlight your experience with AWS services like Redshift, S3, and Glue. Be prepared to discuss specific projects where you designed cloud-based data systems and how you optimised them for performance and cost efficiency.
✨Demonstrate ETL/ELT Knowledge
Discuss your experience in developing and managing ETL/ELT workflows. Bring examples of how you've used AWS Glue or Apache Spark to transform and process data, and be ready to explain the challenges you faced and how you overcame them.
✨Emphasise Data Governance Practices
Since data governance is crucial for this role, be prepared to talk about your understanding of security practices, including encryption and IAM roles. Share any experiences you have with compliance standards like GDPR and SOC 2.
✨Collaborative Mindset
This position requires working closely with data engineers, scientists, and business analysts. Highlight your teamwork skills and provide examples of how you've successfully collaborated across teams to deliver data solutions that meet business needs.
