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For Companies At a Glance
- Tasks: Scale our data and analytics platform while transforming data for stakeholders.
- Company: Fast-growing SaaS company in the UK with a focus on innovation.
- Benefits: Competitive salary, health insurance, pension plan, and more perks.
- Why this job: Join us to make an impact in the exciting world of data analytics.
- Qualifications: Strong SQL skills, experience with dbt or similar tools, and Python proficiency.
- Other info: Dynamic work environment with opportunities for growth and development.
The predicted salary is between 36000 - 60000 £ per year.
A fast-growing SaaS company in the UK is seeking an Analytics Engineer / Data Engineer to aid in scaling their data and analytics platform. This role focuses on SQL modeling, data quality, and transforming analytics data for stakeholder use.
Candidates should have:
- Strong SQL skills
- Hands-on experience with dbt or similar tools
- Proficiency in Python
The position offers a competitive salary with additional perks, including health insurance and a pension plan.
Analytics Engineer / Data Engineer — Analytics‑Ready Data employer: OpenSource
Contact Detail:
OpenSource Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer / Data Engineer — Analytics‑Ready Data
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL models, dbt projects, or any Python scripts you've worked on. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on common technical questions related to data engineering and analytics. Practising with mock interviews can help us feel more confident and ready to impress.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Analytics Engineer / Data Engineer — Analytics‑Ready Data
Some tips for your application 🫡
Show Off Your SQL Skills: Make sure to highlight your SQL expertise in your application. We want to see how you've used SQL modeling in past projects, so don’t hold back on the details!
Talk About Your Tools: If you've got hands-on experience with dbt or similar tools, let us know! Share specific examples of how you've used these tools to transform data and improve analytics.
Python Proficiency is Key: Don’t forget to mention your Python skills! We’re looking for candidates who can demonstrate their ability to use Python effectively in data engineering tasks.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and get to know you better!
How to prepare for a job interview at OpenSource
✨Master Your SQL Skills
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss your experience with SQL modelling and how you've used it in past projects. Practising common SQL queries and being ready to solve problems on the spot can really impress the interviewers.
✨Showcase Your Data Transformation Experience
Since this role focuses on transforming analytics data, be ready to share specific examples of how you've done this in previous roles. Discuss any tools like dbt that you've used and how they helped improve data quality or efficiency in your work.
✨Demonstrate Your Python Proficiency
Python is a key skill for this position, so make sure you can talk about your experience with it. Prepare to discuss any projects where you've used Python for data manipulation or analysis, and be ready to answer technical questions that test your coding knowledge.
✨Understand the Company’s Analytics Needs
Research the company and its analytics platform before the interview. Understanding their specific needs and challenges will allow you to tailor your answers and show how you can add value. This will also help you ask insightful questions, demonstrating your genuine interest in the role.
