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- Tasks: Design and maintain data pipelines using Snowflake on AWS, ensuring data quality and integrity.
- Company: Join a dynamic team in Basildon or Dublin, focused on cutting-edge data solutions.
- Benefits: Enjoy a competitive day rate of GBP 400 and work in a collaborative office environment.
- Why this job: Be at the forefront of data engineering, collaborating with experts and driving impactful projects.
- Qualifications: 5+ years in data engineering with strong Snowflake and AWS skills; degree in a related field required.
- Other info: This role requires hands-on experience with SQL, Python, and various ETL tools.
The predicted salary is between 72000 - 100800 £ per year.
Location: Basildon, UK/Dublin, Ireland
Work from the Client office 5 days a week
Day rate: GBP 400/day
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 fulfil data requirements.
- Optimise 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 modelling.
- 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.
Evaluation will be done according to below:
- Data Architect Must Have
- Data Migration Must Have
- Data Modelling Must-Have
- DBT Knowledge Should Have
- ETL Design Must-Have
- Snowflake Designer/Developer Must Have
- AWS (S3, ETLEMR, Security, Lambda, etc) Must Have
- Leadership/Team handling Must Have
- Communication and Collaboration Must Have
- StreamSet Should Have
- Python Should Have
Snowflake Architect employer: Silicon Logic UK Ltd.
Contact Detail:
Silicon Logic UK Ltd. 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 your conversations. Be prepared to discuss specific projects where you've designed or optimised data pipelines, as this will demonstrate your practical knowledge and problem-solving skills.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who have experience with Snowflake. Attend relevant meetups or webinars, and don't hesitate to reach out on platforms like LinkedIn to connect with potential colleagues or mentors.
✨Tip Number 3
Stay updated on the latest trends and best practices in data engineering and cloud technologies. Being knowledgeable about new features in Snowflake or AWS can give you an edge during discussions and interviews.
✨Tip Number 4
Prepare to discuss your experience with data migration and orchestration tools like Airflow. Highlight any challenges you've faced and how you overcame them, as this will show your ability to handle complex data integration tasks.
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, and data engineering. Use specific examples that demonstrate your skills in designing data pipelines and ETL processes.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about data engineering and how your background aligns with the responsibilities of the Snowflake Architect role. Mention any relevant projects or achievements.
Showcase Technical Skills: Clearly list your technical skills, especially your proficiency in SQL, Python, and ETL tools. If you have experience with Oracle RDBMS or AWS services, make sure to highlight these as well.
Prepare for Technical Questions: Anticipate technical questions related to data warehousing, data migration, and performance optimisation. Be ready to discuss your problem-solving approach and any relevant experiences during interviews.
How to prepare for a job interview at Silicon Logic UK Ltd.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Snowflake and AWS in detail. Highlight specific projects where you've designed data pipelines or implemented data warehousing solutions, and be ready to answer technical questions that demonstrate your proficiency in SQL, Python, and ETL tools.
✨Understand the Company’s Data Needs
Research the company and its data requirements before the interview. Familiarise yourself with their industry and any specific challenges they might face regarding data management. This will help you tailor your responses and show that you're genuinely interested in how you can contribute.
✨Prepare for Problem-Solving Scenarios
Expect to encounter problem-solving scenarios during the interview. Be ready to discuss how you've tackled data pipeline issues in the past, ensuring data quality and integrity. Use the STAR method (Situation, Task, Action, Result) to structure your answers effectively.
✨Demonstrate Collaboration Skills
Since the role involves working closely with data analysts and scientists, be prepared to discuss your experience in collaborative environments. Share examples of how you've successfully worked with stakeholders to define and fulfil data requirements, showcasing your communication and teamwork skills.
