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- Tasks: Lead the development of data pipelines and manage the core data platform.
- Company: Join a dynamic firm focused on financial data innovation.
- Benefits: Enjoy flexible working options and opportunities for professional growth.
- Why this job: Be at the forefront of data engineering, mentoring others while making a real impact.
- Qualifications: Expertise in Python, AWS, SQL, and experience with ETL processes required.
- Other info: Opportunity to collaborate with traders and market data vendors.
The predicted salary is between 48000 - 72000 £ per year.
This client are hiring a Lead Data Engineer for a core team to take ownership of their core data platform, and build data pipelines to parse a broad range of financial data sets into the firm. This will mean exposure to market data vendors, ability to communicate with traders and mentoring junior engineers.
Required Skills:
- Deep Python
- Pandas
- AWS
- Airflow
- Kubernetes
- ETL
- SQL
Lead AWS Data Engineer employer: Paragon Alpha - Hedge Fund Talent Business
Contact Detail:
Paragon Alpha - Hedge Fund Talent Business Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AWS Data Engineer
✨Tip Number 1
Familiarise yourself with the specific AWS services mentioned in the job description, such as AWS Lambda and S3. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your capability to manage data pipelines effectively.
✨Tip Number 2
Brush up on your Python skills, especially with libraries like Pandas. Consider working on personal projects that involve data manipulation and ETL processes to showcase your practical knowledge during interviews.
✨Tip Number 3
Prepare to discuss your experience with Kubernetes and Airflow in detail. Be ready to explain how you've used these technologies to orchestrate data workflows and manage containerised applications in previous roles.
✨Tip Number 4
Since this role involves mentoring junior engineers, think about examples from your past where you've successfully guided others. Highlighting your leadership skills can set you apart from other candidates and show that you're a good fit for the team.
We think you need these skills to ace Lead AWS Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, Python, and data engineering. Include specific projects where you've built data pipelines or worked with financial data sets to demonstrate your relevant skills.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and your understanding of the financial sector. Mention your experience with tools like Airflow and Kubernetes, and how you can contribute to mentoring junior engineers.
Showcase Relevant Projects: If you have worked on projects involving ETL processes or market data vendors, be sure to include these in your application. Use quantifiable results to illustrate your impact, such as improved data processing times or enhanced data accuracy.
Prepare for Technical Questions: Anticipate technical questions related to AWS, SQL, and data engineering practices. Be ready to discuss your problem-solving approach and provide examples of how you've tackled challenges in previous roles.
How to prepare for a job interview at Paragon Alpha - Hedge Fund Talent Business
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, Pandas, AWS, and other relevant technologies. Bring examples of past projects where you've built data pipelines or worked with ETL processes to demonstrate your expertise.
✨Understand Financial Data
Familiarise yourself with the types of financial data sets you might encounter in this role. Being able to discuss how you would handle and parse these data sets will show your understanding of the industry and its requirements.
✨Communicate Effectively
Since the role involves communicating with traders, practice explaining complex technical concepts in simple terms. This will help you demonstrate your ability to bridge the gap between technical and non-technical stakeholders.
✨Mentorship Mindset
Think about your approach to mentoring junior engineers. Be ready to share your philosophy on leadership and how you would support the growth of less experienced team members.
