At a Glance
- Tasks: Build and maintain data pipelines for analytics and reporting systems.
- Company: Join a leading audio AI company with a collaborative culture.
- Benefits: Enjoy a hybrid work environment, competitive salary, and professional growth opportunities.
- Other info: Diverse and inclusive workplace welcoming unique experiences and perspectives.
- Why this job: Make an impact in the audio industry while working with cutting-edge technology.
- Qualifications: Strong SQL, Python skills, and experience with cloud-based data warehouses.
The predicted salary is between 50000 - 60000 € per year.
We are looking for a Data Engineer to help build and maintain the data infrastructure that powers our analytics and reporting systems. You will be responsible for developing reliable data pipelines, maintaining scalable warehouse infrastructure, and enabling teams across Product, Engineering, Commercial, and Leadership to make data-driven decisions. This role focuses on customer behaviour, product analytics, and business intelligence data to support our portfolio of audio-based products.
Key aspects of the role will be to:
- Build and maintain ETL/ELT pipelines for product and customer analytics
- Develop scalable cloud-based data warehouse solutions
- Integrate data from applications, APIs, CRM, billing, and operational systems
- Ensure reliable ingestion, transformation, and storage of data
- Model datasets for reporting and experimentation
- Enable self-service analytics across teams
- Implement validation, monitoring, and alerting for pipelines
- Improve reliability and trustworthiness of datasets
- Optimise warehouse queries and storage performance
- Improve scalability and cost efficiency of data systems
- Support growing data volumes and analytics complexity
Requirements:
- Strong SQL and data modelling capability
- Strong Python or similar scripting/programming language
- Experience with cloud-based data warehouses, especially Big Query
- Experience building ETL/ELT pipelines
- Familiarity with CI/CD and automation workflows
- 2–5+ years in data engineering or analytics engineering
- Experience building and maintaining production data pipelines
- Experience working with analytics and business stakeholders
We encourage you to apply even if you don't meet every single requirement; your unique experiences and perspectives can bring great value to our team. We are committed to fostering a diverse and inclusive workplace and welcome applicants from all backgrounds.
What We Offer:
- Innovative environment: Work on cutting-edge technology in the audio AI space.
- Collaborative culture: Join a supportive and collaborative team dedicated to innovation and excellence.
- Professional growth: Opportunities for continuous learning, skill development, and career advancement.
- Hybrid work environment: 3 days a week at our office in central London (snacks and drinks available).
Data Engineer employer: IRIS Audio Technologies
Join a forward-thinking company at the forefront of audio AI technology, where you will thrive in a collaborative culture that values innovation and excellence. With a strong focus on professional growth, we offer continuous learning opportunities and career advancement while enjoying a hybrid work environment in the heart of central London, complete with complimentary snacks and drinks. We are committed to fostering a diverse and inclusive workplace, making us an excellent employer for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, ETL processes, or any cool projects you've worked on. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Be ready to discuss your past experiences and how they relate to the role. Practice common data engineering questions to boost your confidence.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to join our innovative team.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with SQL, Python, and data pipelines. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re passionate about data engineering and how you can contribute to our team. Be genuine and let your personality come through.
Showcase Your Projects:If you've worked on any cool data projects, make sure to mention them! Whether it's building ETL pipelines or optimising data storage, we love to see practical examples of your work.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at IRIS Audio Technologies
✨Know Your Data Inside Out
Before the interview, make sure you brush up on your SQL and data modelling skills. Be prepared to discuss how you've built and maintained ETL/ELT pipelines in the past, and have examples ready that showcase your experience with cloud-based data warehouses like Big Query.
✨Showcase Your Problem-Solving Skills
Data engineering is all about solving complex problems. Think of specific challenges you've faced in previous roles and how you overcame them. This could be anything from optimising warehouse queries to ensuring reliable data ingestion. Be ready to share these stories!
✨Familiarise Yourself with Their Tech Stack
Research the tools and technologies the company uses, especially around CI/CD and automation workflows. If you have experience with similar tools, highlight that during the interview. It shows you're proactive and genuinely interested in the role.
✨Emphasise Collaboration and Communication
Since this role involves working with various teams, be prepared to discuss how you've collaborated with stakeholders in the past. Share examples of how you've enabled self-service analytics or communicated complex data insights to non-technical teams. This will demonstrate your ability to bridge the gap between data and business needs.
