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- Tasks: Join a team to build a next-gen data platform from scratch using AWS tools.
- Company: Be part of a high-impact initiative shaping the future of data solutions.
- Benefits: Enjoy opportunities to work with cutting-edge technologies and innovative projects.
- Why this job: Make a significant impact on data transformation while developing your skills in a dynamic environment.
- Qualifications: Strong AWS data engineering experience, Python, SQL skills, and a passion for data pipelines.
- Other info: This is a greenfield opportunity to influence architecture and engineering.
The predicted salary is between 48000 - 84000 £ per year.
We're 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'll 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
- 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!
AWS Data Engineer - Market Data employer: Vertus Partners
Contact Detail:
Vertus Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Data Engineer - Market Data
✨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 professionals in the data engineering field, especially those who work with AWS. Attend relevant meetups or webinars to gain insights and potentially get referrals that could help you land the job.
✨Tip Number 3
Stay updated on the latest trends and best practices in data governance and security. Being able to discuss recent developments in these areas during interviews can demonstrate your commitment and expertise.
✨Tip Number 4
Prepare to discuss your previous experiences with building scalable data pipelines. Be ready to share specific examples of challenges you've faced and how you overcame them, as this will highlight your problem-solving skills.
We think you need these skills to ace AWS Data Engineer - Market Data
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 mention how your skills align with the job requirements. Discuss your experience with modern technologies like Databricks and Snowflake, and how you can contribute to the team's goals.
Showcase Relevant Projects: If you have worked on any relevant projects, either professionally or personally, be sure to include them in your application. Describe the challenges you faced and how you overcame them using your technical skills.
Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial in data engineering roles.
How to prepare for a job interview at Vertus Partners
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AWS data engineering tools like Glue, Athena, and PySpark. Highlight specific projects where you've successfully implemented these technologies, as this will demonstrate your hands-on expertise.
✨Demonstrate Problem-Solving Abilities
Expect to face questions that assess your ability to tackle complex data challenges. Prepare examples of how you've approached data governance, quality, and security issues in past roles, showcasing your analytical thinking.
✨Emphasise Your Passion for Data
Convey your enthusiasm for building scalable and efficient data pipelines. Share any personal projects or initiatives that reflect your commitment to data engineering and your desire to innovate within the field.
✨Prepare for Cultural Fit Questions
Research the company's values and culture. Be ready to discuss how your work ethic and team collaboration style align with their mission, as cultural fit is often just as important as technical skills in interviews.
