At a Glance
- Tasks: Design and build impactful data models and optimise data pipelines.
- Company: Join i6 Group, a leader in data engineering innovation.
- Benefits: Enjoy 25 days annual leave and private healthcare.
- Other info: Opportunity to work with cutting-edge tools like dbt, Airflow, and Docker.
- Why this job: Make a real difference with your data skills in a dynamic environment.
- Qualifications: 3-4+ years in Data Engineering and expert SQL skills required.
The predicted salary is between 50000 - 60000 € per year.
i6 Group is seeking an Analytics Engineer to design, build, and maintain complex data models and high-availability data ingestion pipelines. Key responsibilities include implementing DataOps best practices and optimising cloud data warehouse performance.
The ideal candidate must have:
- 3-4+ years in Data Engineering
- Expert-level SQL skills
- Hands-on experience with dbt
- Familiarity with tools like Airflow and Docker
Benefits include 25 days annual leave and private healthcare.
Analytics Engineer: Build High-Impact Data Models employer: i6 Group
i6 Group is an excellent employer that fosters a collaborative and innovative work culture, where Analytics Engineers can thrive while designing impactful data models. With generous benefits such as 25 days of annual leave and private healthcare, alongside ample opportunities for professional growth and development, employees are empowered to excel in their roles. Located in a vibrant area, i6 Group offers a unique environment that encourages creativity and teamwork, making it a rewarding place to build a career.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer: Build High-Impact Data Models
✨Tip Number 1
Network like a pro! Reach out to current or former employees at i6 Group on LinkedIn. A friendly chat can give us insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best data models and projects. We want to see your SQL wizardry and how you’ve tackled real-world problems.
✨Tip Number 3
Ace the interview by practising common questions related to DataOps and cloud data warehousing. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect directly with us.
We think you need these skills to ace Analytics Engineer: Build High-Impact Data Models
Some tips for your application 🫡
Show Off Your SQL Skills:Make sure to highlight your expert-level SQL skills in your application. We want to see how you've used SQL to solve real-world problems, so don’t hold back on sharing specific examples!
Talk About Your Data Engineering Experience:Since we’re looking for someone with 3-4+ years in Data Engineering, be sure to detail your relevant experience. Share projects where you’ve designed and built data models or worked on data ingestion pipelines.
Mention Your Familiarity with Tools:If you’ve got hands-on experience with dbt, Airflow, or Docker, let us know! Mentioning these tools will show us that you’re ready to hit the ground running and implement DataOps best practices.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves!
How to prepare for a job interview at i6 Group
✨Know Your Data Models
Make sure you brush up on your knowledge of data models and how they work. Be ready to discuss your past experiences in designing and building complex data models, as well as any challenges you've faced and how you overcame them.
✨Show Off Your SQL Skills
Since expert-level SQL skills are a must, prepare to demonstrate your proficiency. You might be asked to solve a problem or optimise a query on the spot, so practice common SQL scenarios and be ready to explain your thought process.
✨Familiarity with Tools is Key
Get comfortable with dbt, Airflow, and Docker before the interview. Be prepared to discuss how you've used these tools in your previous roles and how they can help optimise cloud data warehouse performance.
✨Understand DataOps Best Practices
Research DataOps best practices and be ready to talk about how you’ve implemented them in your work. This shows that you’re not just technically skilled but also understand the importance of collaboration and efficiency in data engineering.
