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- Tasks: Join a team to build a next-gen data platform using AWS tools.
- Company: Be part of a cutting-edge company driving data innovation.
- Benefits: Enjoy flexible work options and the chance to work with modern tech.
- Why this job: Shape the future of data solutions and tackle complex challenges.
- Qualifications: Experience with AWS tools, Python, SQL, and a passion for data.
- Other info: This is a greenfield project where you can truly make an impact!
The predicted salary is between 48000 - 84000 £ per year.
We are looking for a Senior AWS Data Engineer to join a high-impact team driving a next-generation data platform initiative. This is a greenfield opportunity to shape the architecture and engineering of a cutting-edge data solution from scratch.
You will be working with modern technologies like Databricks, Snowflake, and the latest in AWS data tooling, helping to solve complex data challenges that have wide-reaching impact across multiple business domains.
Key Requirements:
- Strong experience in AWS data engineering tools (e.g., Glue, Athena, PySpark, Lake Formation)
- Solid skills in Python and SQL for data processing and analysis
- Deep understanding of data governance, quality, and security
- A passion for building scalable, secure, and efficient data pipelines
Nice to Have:
- Broader experience across data platforms or tools
- Familiarity with analytics, ML, or financial data
This is a unique chance to make your mark on a major data transformation!
Data Engineer (with AWS) employer: Vertus Partners
Contact Detail:
Vertus Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (with AWS)
✨Tip Number 1
Familiarise yourself with the specific AWS tools mentioned in the job description, such as Glue and Athena. Consider building a small project or contributing to an open-source project that uses these technologies to showcase your hands-on experience.
✨Tip Number 2
Network with current or former employees of StudySmarter on platforms like LinkedIn. Engaging in conversations about their experiences can provide you with valuable insights into the company culture and expectations for the role.
✨Tip Number 3
Stay updated on the latest trends in data engineering and AWS technologies. Following relevant blogs, attending webinars, or joining online communities can help you discuss current topics during interviews, demonstrating your passion and knowledge.
✨Tip Number 4
Prepare to discuss your approach to data governance and security, as these are crucial aspects of the role. Think of examples from your past work where you successfully implemented data quality measures or secured sensitive information.
We think you need these skills to ace Data Engineer (with AWS)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS data engineering tools like Glue, Athena, and PySpark. Include specific projects where you've built scalable data pipelines or worked on data governance.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how you can contribute to the next-generation data platform initiative. Mention any relevant experience with modern technologies like Databricks and Snowflake.
Showcase Technical Skills: Clearly outline your proficiency in Python and SQL within your application. Provide examples of how you've used these languages for data processing and analysis in previous roles.
Highlight Problem-Solving Abilities: Discuss specific challenges you've faced in data engineering and how you overcame them. This will demonstrate your ability to tackle complex data challenges effectively.
How to prepare for a job interview at Vertus Partners
✨Showcase Your AWS Expertise
Make sure to highlight your experience with AWS data engineering tools like Glue, Athena, and PySpark. Be prepared to discuss specific projects where you've successfully implemented these technologies and the impact they had on the business.
✨Demonstrate Your Python and SQL Skills
Since strong skills in Python and SQL are key requirements, be ready to provide examples of how you've used these languages for data processing and analysis. Consider discussing any complex queries or scripts you've written that solved significant data challenges.
✨Understand Data Governance and Security
A deep understanding of data governance, quality, and security is crucial. Prepare to talk about your approach to ensuring data integrity and compliance, as well as any frameworks or best practices you follow in your work.
✨Express Your Passion for Data Engineering
This role is about building scalable and efficient data pipelines, so convey your enthusiasm for data engineering. Share your thoughts on current trends in the field and how you stay updated with new technologies and methodologies.
