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For Companies At a Glance
- Tasks: Design and implement data solutions using Snowflake and AWS, focusing on data migration and warehousing.
- Company: Join a leading tech firm that values innovation and collaboration in the data engineering space.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team that tackles exciting challenges and makes a real impact in data management.
- Qualifications: 5+ years in data engineering with expertise in Snowflake, SQL, Python, and AWS services.
- Other info: Ideal for problem solvers who thrive in fast-paced environments and love working with cutting-edge technology.
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.
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 common Snowflake and AWS-related problems. Use platforms like LeetCode or HackerRank to sharpen your SQL and Python skills, ensuring you're ready to tackle any challenges during the interview process.
We think you need these skills to ace Snowflake Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, specifically with Snowflake and AWS. Include relevant projects where you've used SQL, Python, and ETL tools like Streamsets or DBT.
Craft a Compelling Cover Letter: In your cover letter, emphasise your hands-on experience with Oracle RDBMS and data migration to Snowflake. Mention specific AWS services you have worked with, such as S3, Lambda, Redshift, and Glue.
Showcase Problem-Solving Skills: Provide examples in your application that demonstrate your problem-solving abilities and how you've delivered high-quality solutions in previous roles. This could be through specific challenges you faced and how you overcame them.
Highlight Communication Skills: Since excellent communication skills are essential for this role, include instances where you've effectively communicated complex technical concepts to non-technical stakeholders or collaborated with teams to achieve project goals.
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 and Python, and be ready to provide examples of how you've used ETL tools like Streamsets or DBT in past projects.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your problem-solving skills. Think of real-life challenges you've encountered in data engineering and how you resolved them, particularly in relation to data migration and warehousing.
✨Communicate Clearly
Strong communication skills are essential for this role. Practice explaining complex technical concepts in simple terms, as you may need to convey your 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 these factors influence your design decisions and project outcomes.
