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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, SQL, AWS, 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 include:
- Deep Python
- Pandas
- AWS
- Airflow
- Kubernetes
- ETL
- SQL
Lead Data Engineer SQL AWS 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 Data Engineer SQL AWS
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as AWS, Airflow, and Kubernetes. Having hands-on experience or projects showcasing your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the financial data sector. Attend industry meetups or webinars where you can connect with traders and data engineers. This can provide valuable insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your experience with mentoring junior engineers. Think of specific examples where you've guided others, as this is a key aspect of the role. Being able to articulate your leadership style will demonstrate your readiness for the position.
✨Tip Number 4
Stay updated on the latest trends in data engineering and financial data management. Being knowledgeable about current challenges and innovations in the field will show your passion and commitment to the role during interviews.
We think you need these skills to ace Lead Data Engineer SQL AWS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL, AWS, and Python. Include specific projects where you've built data pipelines or worked with financial data sets to demonstrate your relevant skills.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention your experience in mentoring junior engineers and your ability to communicate effectively with traders, as these are key aspects of the job.
Showcase Technical Skills: Be specific about your technical skills in your application. Detail your experience with tools like Pandas, Airflow, and Kubernetes, and provide examples of how you've used them in past roles.
Highlight Relevant Experience: If you have experience working with market data vendors or in a financial environment, make sure to highlight this in your application. This will show that you understand the industry and its challenges.
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, SQL, and AWS in detail. Highlight specific projects where you've built data pipelines or worked with ETL processes, as this will demonstrate your hands-on expertise.
✨Understand the Financial Domain
Familiarise yourself with financial data sets and market data vendors. Being able to speak knowledgeably about how data impacts trading decisions will impress the interviewers and show that you can communicate effectively with traders.
✨Demonstrate Leadership Qualities
Since this role involves mentoring junior engineers, be ready to share examples of how you've led teams or supported colleagues in their development. Discuss your approach to leadership and how you foster a collaborative environment.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in previous roles, particularly related to data engineering, and how you overcame them using tools like Airflow and Kubernetes.
