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- Tasks: Design and implement data solutions using Snowflake and AWS, ensuring high-quality outcomes.
- Company: Join a leading tech firm focused on innovative data engineering solutions.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team that values creativity and problem-solving in data architecture.
- Qualifications: 5+ years in data engineering with expertise in Snowflake, SQL, Python, and AWS services.
- Other info: Ideal for tech enthusiasts eager to tackle complex data challenges.
The predicted salary is between 48000 - 72000 £ per year.
5+ years of experience in data engineering, with a strong focus on Snowflake and AWS.
- Proficiency in SQL, Python, and ETL tools (Streamsets, DBT etc.)
- Hands-on experience with Oracle RDBMS
- Data Migration experience to Snowflake
- Experience with AWS services such as S3, Lambda, Redshift, and Glue
- Strong understanding of data warehousing concepts and data modeling
- Excellent problem-solving and communication skills, with a focus on delivering high-quality solutions
- Understanding/hands-on experience in Orchestration solutions such as Airflow
- Deep knowledge of key non-functional requirements such as availability, scalability, operability, and maintainability
Snowflake Architect employer: Smartedge Solutions
Contact Detail:
Smartedge Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Snowflake Architect
✨Tip Number 1
Network with professionals in the data engineering field, especially those who have experience with Snowflake and AWS. Attend industry meetups or webinars to connect with potential colleagues and learn about their experiences.
✨Tip Number 2
Showcase your hands-on experience with Snowflake and AWS by working on personal projects or contributing to open-source projects. This practical experience can set you apart from other candidates.
✨Tip Number 3
Familiarise yourself with the latest trends and updates in data warehousing and cloud technologies. Being knowledgeable about new features in Snowflake and AWS can demonstrate your commitment to staying current in the field.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving scenarios related to data migration and orchestration solutions like Airflow. Being able to articulate your thought process during these scenarios can impress interviewers.
We think you need these skills to ace Snowflake Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your 5+ years of experience in data engineering, specifically focusing on Snowflake and AWS. Include relevant projects and technologies you've worked with, such as SQL, Python, and ETL tools like Streamsets and DBT.
Craft a Strong Cover Letter: In your cover letter, emphasise your hands-on experience with Oracle RDBMS and data migration to Snowflake. Discuss your familiarity with AWS services like S3, Lambda, Redshift, and Glue, and how these experiences make you a great fit for the role.
Showcase Problem-Solving Skills: Provide examples in your application that demonstrate your excellent problem-solving abilities. Highlight specific challenges you've faced in previous roles and how you delivered high-quality solutions.
Highlight Orchestration Experience: If you have experience with orchestration solutions like Airflow, make sure to mention it. Discuss how this knowledge contributes to your understanding of data warehousing concepts and non-functional requirements such as availability and scalability.
How to prepare for a job interview at Smartedge Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Snowflake, AWS, and the specific tools mentioned in the job description. Highlight your proficiency in SQL, Python, and ETL tools like Streamsets and DBT, as well as your hands-on experience with Oracle RDBMS.
✨Demonstrate Data Migration Experience
Share specific examples of data migration projects you've worked on, particularly those involving Snowflake. Discuss the challenges you faced and how you overcame them to ensure a smooth transition.
✨Understand Data Warehousing Concepts
Make sure you can explain key data warehousing concepts and data modelling techniques. Be ready to discuss how these concepts apply to the role and how you've implemented them in past projects.
✨Communicate Problem-Solving Skills
Prepare to discuss scenarios where you've solved complex problems related to data engineering. Emphasise your communication skills and how they helped you collaborate effectively with team members and stakeholders.
