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- Tasks: Design and maintain data pipelines using Snowflake on AWS, ensuring data quality and integrity.
- Company: Join a fast-growing company at the forefront of data engineering and cloud technologies.
- Benefits: Enjoy flexible working options and opportunities for professional growth in a dynamic environment.
- Why this job: Be part of a collaborative team that values innovation and offers impactful projects in data warehousing.
- Qualifications: Bachelor's degree in a related field and 5+ years of experience in data engineering required.
- Other info: Hands-on experience with AWS services and ETL tools is essential for success in this role.
The predicted salary is between 43200 - 72000 £ per year.
A Snowflake Architect is required for a long-term project with a fast-growing company.
Responsibilities:
- Design, develop, and maintain robust data pipelines and ETL processes using Snowflake on AWS.
- Implement data warehousing solutions, ensuring efficient storage, retrieval, and transformation of large datasets.
- Collaborate with data analysts, scientists, and other stakeholders to define and fulfill data requirements.
- Optimize performance and scalability of Snowflake data warehouse, ensuring high availability and reliability.
- Develop and maintain data integration solutions, ensuring seamless data flow between various sources and Snowflake.
- Monitor, troubleshoot, and resolve data pipeline issues, ensuring data quality and integrity.
- Stay up-to-date with the latest trends and best practices in data engineering and cloud technologies.
Qualifications:
- Bachelor’s degree in computer science, Engineering, or a related field.
- 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: Empiric
Contact Detail:
Empiric 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 related tools by working on personal projects or contributing to open-source projects. This practical experience can set you apart from other candidates.
✨Tip Number 3
Stay updated on the latest trends in data engineering and cloud technologies. Follow relevant blogs, podcasts, and forums to gain insights that you can discuss during interviews, demonstrating your passion for the field.
✨Tip Number 4
Prepare for technical interviews by practising common Snowflake and AWS-related questions. Use platforms like LeetCode or HackerRank to sharpen your SQL and Python skills, ensuring you're ready to tackle any challenges presented.
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 with Snowflake, AWS, SQL, and Python. Use specific examples from your past roles that demonstrate your expertise in data engineering and ETL processes.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about data engineering and how your skills align with the responsibilities of the Snowflake Architect role. Mention any relevant projects or achievements that showcase your capabilities.
Showcase Relevant Projects: If you have worked on significant projects involving data warehousing or cloud technologies, summarise these in your application. Highlight your role, the technologies used, and the outcomes achieved to demonstrate your hands-on experience.
Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism, which is crucial for a technical role like this.
How to prepare for a job interview at Empiric
✨Showcase Your Technical Skills
Make sure to highlight your experience with Snowflake, AWS, SQL, and Python during the interview. Be prepared to discuss specific projects where you've implemented ETL processes or data warehousing solutions, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Data Needs
Research the company and its data requirements before the interview. Understanding their business model and how they utilise data will allow you to tailor your responses and show that you're genuinely interested in contributing to their success.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially related to data pipeline issues and performance optimisation. Think of examples from your past experiences where you successfully resolved challenges, and be ready to explain your thought process.
✨Demonstrate Collaboration Skills
Since the role involves working with data analysts and scientists, be prepared to discuss how you’ve collaborated with cross-functional teams in the past. Highlight your communication skills and how you ensure that data requirements are met effectively.
