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- Tasks: Ingest, model, and publish data while collaborating on product metrics.
- Company: Leading financial tech company in London with a vibrant culture.
- Benefits: Ownership, excellence, and a dynamic work environment.
- Other info: Opportunity to work with Python and Snowflake in a collaborative setting.
- Why this job: Join a team that values innovation and makes an impact in fintech.
- Qualifications: 5+ years of experience and strong engineering best practices.
The predicted salary is between 43200 - 72000 £ per year.
A leading financial technology company in London seeks a Data Engineer to join their product delivery team. The role involves ingesting, modeling, and publishing data while collaborating closely with stakeholders to define meaningful product metrics.
Candidates should have at least 5 years of experience, a solid understanding of engineering best practices, and a bonus for familiarity with tech stack including Python and Snowflake.
This role offers a chance to work in a vibrant culture focused on ownership and excellence.
Analytics Engineer - Data Pipelines & Dashboards employer: STARTmunich e.V
Contact Detail:
STARTmunich e.V Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer - Data Pipelines & Dashboards
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at the company you're eyeing. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and dashboards. Use real-world examples to demonstrate how you've tackled challenges and delivered results.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge. Be ready to discuss your experience with Python and Snowflake, and think of examples where you've applied engineering best practices.
✨Tip Number 4
Don't forget to 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 with us directly.
We think you need these skills to ace Analytics Engineer - Data Pipelines & Dashboards
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data pipelines and dashboards. We want to see how your skills align with the role, so don’t be shy about showcasing your familiarity with Python and Snowflake!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our vibrant culture. Let us know what excites you about this opportunity!
Showcase Your Projects: If you've worked on relevant projects, include them in your application. We love seeing real examples of your work, especially if they demonstrate your understanding of engineering best practices and collaboration with stakeholders.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at STARTmunich e.V
✨Know Your Tech Stack
Make sure you brush up on your knowledge of Python and Snowflake. Be ready to discuss how you've used these technologies in past projects, as well as any challenges you faced and how you overcame them.
✨Understand the Business Metrics
Since the role involves defining meaningful product metrics, take some time to research common metrics in the financial technology sector. Be prepared to share your thoughts on what metrics are most important and why.
✨Showcase Your Collaboration Skills
This position requires close collaboration with stakeholders. Think of examples from your previous roles where you successfully worked with others to achieve a common goal. Highlight your communication skills and how you ensure everyone is on the same page.
✨Demonstrate Engineering Best Practices
Be ready to discuss engineering best practices you've implemented in your work. This could include topics like code reviews, testing, or documentation. Showing that you value quality and efficiency will resonate well with the interviewers.