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For Companies At a Glance
- 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 43200 - 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.
Locations
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
Make sure to showcase your hands-on experience with Snowflake and AWS in any conversations or networking opportunities. Highlight specific projects where you've successfully implemented these technologies, as real-world examples can make a strong impression.
✨Tip Number 2
Engage with the Snowflake community through forums, webinars, or local meetups. This not only helps you stay updated on the latest trends but also allows you to connect with professionals who might refer you to job openings at StudySmarter.
✨Tip Number 3
Brush up on your SQL and Python skills by working on personal projects or contributing to open-source initiatives. Being able to demonstrate your coding abilities can set you apart from other candidates during interviews.
✨Tip Number 4
Familiarise yourself with orchestration tools like Airflow, as well as data migration strategies to Snowflake. Having a solid understanding of these concepts will not only boost your confidence but also show potential employers that you're well-prepared for the role.
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 problem-solving abilities and communication skills. Highlight specific instances where you delivered high-quality solutions in previous roles.
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, SQL, and Python in detail. Highlight specific projects where you utilised these technologies, especially focusing on data migration and ETL processes.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your problem-solving skills. Prepare examples of challenges you've faced in data engineering and how you resolved them, particularly in relation to data warehousing and orchestration solutions like Airflow.
✨Communicate Clearly
Strong communication skills are essential for this role. Practice explaining complex technical concepts in simple terms, as you may need to convey ideas to non-technical stakeholders during the interview.
✨Understand Non-Functional Requirements
Familiarise yourself with key non-functional requirements such as availability, scalability, operability, and maintainability. Be ready to discuss how you have ensured these aspects in your previous projects.
