At a Glance
- Tasks: Design and maintain data models that power decision-making across the company.
- Company: Join Noon, a mission-driven company transforming education for millions.
- Benefits: Flexible hybrid or remote work options, competitive salary, and a supportive team.
- Other info: Diverse and inclusive workplace committed to equal opportunities for all.
- Why this job: Make a real impact on education while working with cutting-edge data technologies.
- Qualifications: Strong SQL, Python skills, and experience in building reliable data systems.
The predicted salary is between 60000 - 80000 € per year.
Please note this position has two working model options: hybrid if you are in London (one a week work‑from‑office), or remote in Europe. For other regions, please check other opportunities in our career site.
About Noon
Noon's mission is to radically change the way people learn, with a primary focus on the Middle East, where the company has its roots and where the need and urgency to improve education are highest. We have taught over 12 million students successfully with our remote learning products. Our next big challenge is to build a network of schools, supported by top teachers and driven by technology and innovation, to positively impact even more lives.
Why work at Noon
- The opportunity to have a real impact on millions of students.
- A strong leadership and engineering team to learn from.
- A solid runway: we recently closed our Series B and have substantial recurring revenue.
About The Role
We’re looking for a Senior Data Analytics Engineer to join our data & analytics team and help build the data foundations that power decision‑making across the company. In this role, you’ll own the curated datasets, metric definitions, and data models that act as the company’s single source of truth. Your work will ensure that analysts, product managers, and leadership can trust the numbers they rely on every day. You’ll collaborate closely with engineers, analysts, product managers, and operations teams to improve how data is structured, validated, and accessed. A key part of the role is making our data systems scalable and reliable so teams can move faster with confidence. This position offers flexibility with a hybrid/fully remote work setup while still collaborating closely with cross‑functional teams.
What You’ll Do
- Build the company’s single source of truth: Design and maintain curated datasets and data models that power reporting, dashboards, and analysis across the business.
- Define and standardize key metrics: Work with stakeholders to ensure important business metrics are clearly defined, consistent, and trusted across teams.
- Improve data reliability: Implement validation checks, monitoring, and processes that prevent data issues and quickly detect anomalies.
- Lead cross‑functional data projects: Take ownership of high‑impact initiatives from problem definition through delivery, aligning with product, engineering, and operations teams along the way.
- Investigate and resolve data issues: Diagnose discrepancies in metrics, identify root causes, and work with engineers and analysts to implement long‑term fixes.
- Enable better self‑serve analytics: Improve documentation, dataset structure, and discoverability so teams can explore and answer their own questions confidently.
- Support our AI data tools: Help ensure our internal AI data analyst produces accurate answers by grounding it in trusted datasets and consistent metric definitions.
- Mentor and support the data team: Share best practices with analysts and help raise the overall quality and reliability of our analytics work.
What We’re Looking For
- Strong SQL, Python and data modelling skills: You’re highly proficient in SQL and comfortable using Python and designing datasets that are reliable, scalable, and easy for others to use.
- Experience building reliable data systems: You’ve worked with production datasets or pipelines and understand how to monitor, validate, and maintain them (e.g., Python, Airflow, AWS).
- Cross‑functional mindset: You’re comfortable collaborating with product managers, engineers, analysts, and business stakeholders.
- Strong problem‑solving ability: You enjoy digging into messy data problems, figuring out why numbers don’t match, and understanding what each metric truly represents.
- Clear communicator: You can explain data logic and metric definitions in ways that make sense to both technical and non‑technical audiences.
- Ownership and pragmatism: You exercise good judgment, balancing speed and accuracy while focusing on solutions that are both reliable and practical.
Bonus points if you:
- Have experience working with AI‑driven analytics tools or assistants.
- Experience building pipelines that integrate internal data with AI systems.
- Experience working with both frontend and backend events.
About Diversity & Inclusion
We understand that everyone has a unique set of skills and experiences. If you’re passionate about making a real positive impact through education, even if you don’t meet all the requirements above, we encourage you to apply. At Noon, we respect and value differences. We know that when people from different backgrounds and with different points of view work together, we create the most value – for our clients, our people, and society. Noon is proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of age, disability, gender identity, marital status, race, colour, ethnicity, religion, sex, national origin, or sexual orientation. We aim to be truly representative of the world and for each and every employee to feel respected.
Senior Data Analytics Engineer employer: Noon - Education for Everyone
At Noon, we are dedicated to transforming education and making a meaningful impact on millions of students, particularly in the Middle East. Our hybrid and remote work options provide flexibility while fostering a collaborative environment with a strong focus on innovation and professional growth. Join us to be part of a dynamic team that values diversity, encourages mentorship, and offers the chance to work with cutting-edge technology in a supportive culture.
Contact Detail:
Noon - Education for Everyone Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to people in your field on LinkedIn or at industry events. A friendly chat can lead to opportunities you might not find on job boards.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your skills. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 3
Showcase your projects! If you've worked on data models or analytics tools, bring them up during interviews. Real examples of your work can set you apart from the competition.
✨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 Senior Data Analytics Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Data Analytics Engineer role. Highlight your SQL, Python, and data modelling skills, and don’t forget to mention any experience with AI-driven analytics tools!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re passionate about education and how your background can help us achieve our mission. Be genuine and let your personality shine through – we want to get to know the real you!
Showcase Your Problem-Solving Skills:In your application, share examples of how you've tackled messy data problems in the past. We love candidates who can dig deep and find solutions, so don’t hold back on those success stories!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be one step closer to joining our amazing team at Noon!
How to prepare for a job interview at Noon - Education for Everyone
✨Know Your Data Inside Out
As a Senior Data Analytics Engineer, you’ll need to demonstrate your expertise in SQL and Python. Brush up on your data modelling skills and be ready to discuss specific projects where you've built reliable data systems. Prepare to explain how you’ve tackled data discrepancies and the methods you used to ensure data integrity.
✨Showcase Your Cross-Functional Collaboration
This role requires working closely with various teams, so be prepared to share examples of how you've successfully collaborated with product managers, engineers, and analysts. Highlight any cross-functional projects you've led and how you ensured everyone was aligned on key metrics and definitions.
✨Communicate Clearly and Confidently
You’ll need to explain complex data concepts to both technical and non-technical audiences. Practice articulating your thought process and the logic behind your data models. Use simple language and relatable examples to make your points clear during the interview.
✨Demonstrate Problem-Solving Skills
Prepare to discuss specific instances where you've identified and resolved data issues. Think about the steps you took to diagnose problems and the long-term fixes you implemented. This will show your potential employer that you have the analytical mindset they’re looking for.