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- Tasks: As a Data Engineer, you'll manage the data warehouse and influence tech stack decisions.
- Company: Join a rapidly growing insurance company that's expanding its data team!
- Benefits: Enjoy remote work with just one office day per month and flexible hours.
- Why this job: This role offers independence and the chance to shape data engineering practices.
- Qualifications: Must have over 3 years of experience in data engineering and strong skills in Python and SQL.
- Other info: Be the sole data engineer and make a significant impact on the team's success.
The predicted salary is between 43200 - 72000 £ per year.
Role: Data Engineer Location: Remote (in office 1 day month)
This rapidly growing insurance company is looking to expand their data team to support their extensive growth! They are looking to bring in a Data Engineer and the ideal candidate would have over 3 years experience.
You will also have experience working independently as you will be the sole data engineer and have worked extensively on the data warehouse. You will have core Data Engineering responsibilities and have the opportunity to influence the techstack being used
Python
# SQL
# Sign off chat
Senior Engineer, Data Engineering employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Engineer, Data Engineering
✨Tip Number 1
Make sure to highlight your experience with data warehouses in your conversations. Since you'll be the sole data engineer, showcasing your ability to manage and optimize data storage solutions will be crucial.
✨Tip Number 2
Familiarize yourself with the tech stack mentioned in the job description, especially Python and SQL. Being able to discuss specific projects where you've utilized these technologies will demonstrate your hands-on experience.
✨Tip Number 3
Since this role requires independent work, prepare examples of how you've successfully managed projects on your own. This will show that you can thrive in a remote setting while being the go-to person for data engineering.
✨Tip Number 4
Engage with the company's culture and values during your discussions. Understanding their growth trajectory and how you can contribute to it will help you stand out as a candidate who is not only skilled but also aligned with their mission.
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Understand the Role: Make sure you fully understand the responsibilities of a Data Engineer as outlined in the job description. Highlight your experience with data warehouses and any relevant projects you've worked on.
Showcase Your Experience: In your CV and cover letter, emphasize your 3+ years of experience in data engineering. Provide specific examples of how you've worked independently and contributed to data projects.
Highlight Technical Skills: Clearly list your technical skills, especially in Python and SQL. Mention any relevant tools or technologies you've used that align with the company's tech stack.
Tailor Your Application: Customize your application materials to reflect the company's needs. Use keywords from the job description to demonstrate that you are a perfect fit for the role.
How to prepare for a job interview at Harnham
✨Showcase Your Experience
Make sure to highlight your experience with data engineering, especially your work with data warehouses. Be prepared to discuss specific projects where you played a key role and the technologies you used.
✨Demonstrate Independence
Since you'll be the sole data engineer, it's crucial to convey your ability to work independently. Share examples of how you've successfully managed projects on your own and made decisions that positively impacted your previous teams.
✨Familiarize Yourself with the Tech Stack
Research the technologies mentioned in the job description, particularly Python and SQL. Be ready to discuss your proficiency with these tools and any relevant frameworks or libraries you have experience with.
✨Prepare for Technical Questions
Expect technical questions related to data engineering concepts, data modeling, ETL processes, and performance optimization. Brush up on these topics and be ready to solve problems or provide insights during the interview.
