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- Tasks: Build and manage scalable data pipelines that power pricing for 3,000+ hotels worldwide.
- Company: Join a forward-thinking tech company with a focus on data-driven solutions.
- Benefits: Enjoy a competitive salary, remote work flexibility, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on quality and career advancement.
- Why this job: Make a real impact by reshaping how data flows through our innovative product.
- Qualifications: 2-4 years of Python experience in data engineering and strong ETL/ELT pipeline skills.
The predicted salary is between 50000 - 60000 £ per year.
Location: Remote Germany, Remote UK, Remote Spain, Remote Austria, Remote Portugal, Remote Netherlands, Remote Romania
Employment Type: Full time
Location Type: Remote
Department: Product
You'll understand who relies on your work and what decisions it enables. Our data powers pricing recommendations for 3,000+ hotels worldwide, helping independent hoteliers set the right pricing. When you ship something here, you'll see the direct impact on real businesses and the people who run them.
Your Responsibilities
- Build and own design scalable data pipelines using our modern stack (Snowflake, Dagster, dbt) and take them from idea to production to monitoring. You'll own the full lifecycle.
- Modernize with purpose. Help us migrate legacy Django/Celery pipelines to our modern platform. This is an opportunity to reshape how data flows through our entire product.
- Bridge the gap. Work closely with Product, Analytics, and Engineering (Backend, Frontend, and Data Science). Translate business questions into technical designs. Ensure analysts and data scientists can actually use what you build.
- Care about quality. Champion data reliability through testing, observability, and documentation. Multiple teams depend on your work daily; accuracy and trust are non-negotiable.
Your Profile
- 2-4 years of professional Python experience, ideally in data engineering and/or backend systems.
- Experience building and maintaining ETL/ELT pipelines in production environments, preferably on modern cloud data warehouses (e.g., Snowflake, Databricks, BigQuery, Redshift).
- Solid understanding of data modeling concepts, including analytics-ready schema design (fact/dimension modeling) and performance optimization.
- Experience working with orchestrated data pipelines (e.g., Dagster, Airflow, or similar tools).
- Experience building backend or ingestion services using Python web frameworks such as Django, FastAPI, or Flask.
- Familiarity with background task processing and asynchronous workflows (e.g., Celery or similar systems).
- Experience working with cloud infrastructure, preferably AWS (e.g., S3, RDS/Aurora).
- Understanding of software design principles and data pipeline architecture fundamentals.
- Experience working with large datasets using tools such as pandas, polars, or NumPy.
- Analytical mindset with an interest in data quality, KPIs, and data-driven decision-making.
- Ownership mentality—you care about writing reliable, maintainable code and improving what you touch.
- Familiarity with product-oriented data teams serving multiple stakeholders.
- Fluent in English and comfortable participating in technical discussions.
- Based within the European Time Zone (UTC+0 to UTC+2).
Nice to Have
- Hands‑on experience with dbt (modeling, testing, documentation, performance tuning).
- Experience with or interest in modernizing legacy data pipelines.
- Hands‑on experience with Celery.
Remote Mid Data Engineer (m/f/d) in Kent employer: Founderful
Contact Detail:
Founderful Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Mid Data Engineer (m/f/d) in Kent
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or through relevant forums. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those using Python and modern data stacks. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in the past.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Remote Mid Data Engineer (m/f/d) in Kent
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match our job description. Highlight your Python experience, data pipeline work, and any relevant projects you've tackled. We want to see how you can fit into our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're excited about the role and how your background aligns with our mission at StudySmarter. Show us your personality and passion for data engineering!
Showcase Your Projects: If you've worked on any cool data projects, don’t hold back! Include links or descriptions of your work, especially if it involves modern tools like Snowflake or Dagster. We love seeing real examples of your skills in action.
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 ensures you’re considered for the role. Plus, it’s super easy—just a few clicks and you’re done!
How to prepare for a job interview at Founderful
✨Know Your Tech Stack
Make sure you’re familiar with the tools mentioned in the job description, like Snowflake, Dagster, and dbt. Brush up on your Python skills and be ready to discuss how you've used these technologies in past projects. This shows you’re not just a fit on paper but can actually contribute from day one.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in data engineering and how you tackled them. Think about times when you had to bridge gaps between teams or modernise legacy systems. This will demonstrate your analytical mindset and ownership mentality, which are key for this role.
✨Understand the Business Impact
Since the role involves making decisions that affect real businesses, be ready to explain how your work has previously impacted business outcomes. Discuss how you’ve translated business questions into technical designs, ensuring that your solutions are not only technically sound but also aligned with business goals.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy, team dynamics, and future projects. This shows your genuine interest in the role and helps you assess if the company is the right fit for you. Plus, it gives you a chance to engage with your interviewers on a deeper level.