At a Glance
- Tasks: Lead the design and delivery of scalable data solutions that transform higher education.
- Company: Join QS, a global leader in higher education analytics and insights.
- Benefits: Enjoy competitive salary, flexible working, wellness initiatives, and professional growth opportunities.
- Why this job: Make a real impact in education while leading a dynamic team of innovators.
- Qualifications: Proven leadership in data engineering with strong skills in SQL and Python.
- Other info: Be part of a diverse community dedicated to empowering individuals through education.
The predicted salary is between 43200 - 72000 ÂŁ per year.
This position offers a hybrid work model, allowing flexibility between working from home and our office. Typically, employees are expected to work 2 days in the office per week.
At QS, we believe that work should empower you. That’s why we foster a flexible working environment that encourages every employee to own their career whilst flourishing personally and professionally. Our company values underpin everything we do – we collaborate, respect and support each other. It’s our mission to empower motivated people around the world to fulfil their potential through higher education, ensuring that everyone has access to opportunities that change lives. Our diversity makes us stronger. By sharing our experiences, we learn from one another and achieve more together, driving progress across the sector.
As Head of Data Engineering, you will lead in the architectural design, build, and delivery of scalable data pipelines, APIs, and services at the core of QS Cerebrum, and our enterprise analytics and AI platforms. The Head of Data Engineering will be accountable for building and owning the data architecture and infrastructure that underpin QS’s core student and institution facing products and enterprise analytics. This role leads the engineering function responsible for ingestion, transformation, quality, governance, and delivery of all core QS datasets. You will define and embed engineering standards, robust governance and data quality measures into all pipelines, and actively develop your engineers to deliver a high‑performance culture in Data and Analytics. This role will collaborate with leaders across Data Science, Product and Technology to build the QS data platform. Your strong leadership and communication skills will be essential in collaborating with stakeholders, guiding team members, and contributing to QS’s long‑term strategic objectives.
Role responsibilities:
- Data Platform Ownership: Architect and evolve QS’s enterprise data platform (AWS + Snowflake). Drive the transition toward modern data architectures (data platform, streaming pipelines, real‑time scoring where relevant). Own standards for ingestion, transformation, orchestration, metadata, observability, and lineage.
- Pipeline & Infrastructure Leadership: Build robust ETL/ELT pipelines for QS datasets across performance, recruitment, skills and innovation, including real‑time student demand data, global workforce data and higher education rankings data. Implement scalable frameworks for data acquisition from surveys, universities, partners, and public sources. Ensure pipelines are cost‑efficient, monitored, recoverable, and version‑controlled.
- Data Quality & Governance: Establish enterprise‑wide data quality metrics, monitoring systems, and remediation workflows. Implement governance frameworks aligned with QS’s methodologies and product/service requirements. Partner with Data Science, Technology and Product to standardize definitions, master data, and reference data models.
- Team Leadership: Lead, grow, and mentor a global team of data engineers. Set clear engineering standards, code practices, review processes, and architectural guidelines. Build a culture of technical excellence, reliability, and delivery accountability.
- Cross‑Functional Collaboration: Partner with the Director of Data Science, Technology and Product Leads to align on priorities, platform capabilities, and data readiness. Translate business and methodological requirements into scalable data engineering solutions. Work with compliance and security teams on data privacy, PII handling, and regulatory alignment (GDPR, global privacy standards).
- Strategic Contribution: Own and drive the multi‑year data engineering roadmap. Introduce automation, ML‑assisted data validation, and higher‑frequency data refresh cycles to improve QS’s data competitiveness. Future‑prove QS’s data stack to support new growth models.
Key skills and experience:
- Proven ability to lead teams and deliver results in complex data or information services businesses.
- Wicked problem‑solver who thrives in dynamic, evolving environments.
- Strategic communicator with strong interpersonal and leadership skills, fostering collaboration and inclusivity.
- Demonstrable business impact, balancing technical solutions with practical business needs.
- Strong proficiency in SQL and Python, with hands‑on experience in cloud data platforms (such as Snowflake or equivalent).
- Strong experience with orchestration tools (e.g., Glue, Airflow, dbt) supporting reliable data workflows, streaming frameworks (such as Kafka, Snowpipe) for real‑time data delivery and machine learning and artificial intelligence workflows, including feature stores and platforms like SageMaker.
- Excellent understanding of data modeling concepts, including graph‑based design.
- Familiarity with REST/GraphQL APIs and approaches to optimise data delivery and performance.
- Master’s degree or higher in a relevant field.
Please note, if you don’t meet all the criteria but believe you have the skills and passion to thrive in this role, we encourage you to apply.
QS is the world leader in higher education services, analytics, insights and intelligence. From consultancy to student mobility, academic partnerships to branding solutions, our services power both institutional and individual success. We’re behind the world’s most widely read university rankings (Meltwater 2023). Our QS World University Rankings® reach hundreds of millions, shaping decisions and guiding futures. Since launching in 1990, our impact and influence have only grown. Today, we work with more than 2,000 of the world’s leading higher education institutions, over 12,000 employers, and governments seeking change and socioeconomic development through higher education.
Join QS and you’ll join an 800‑strong community of problem‑solvers, creators, collaborators and change‑makers based in 40+ countries and 11 international offices, including Australia, Malaysia, India, Romania, Singapore, France, Germany, the USA and our headquarters in London. With every talented new hire, business acquisition and bold initiative, we’re strengthening our reach and delivering even greater value to institutions and learners worldwide.
We take investing in our people very seriously. As standard you will have:
- Competitive base salary.
- Access to an annual bonus scheme (for qualifying roles only).
- 25 days annual leave, plus bank holidays – increasing to 27 days after 5 years.
- Access to a Buy Holiday scheme allowing you to buy up to 5 additional holiday days per year.
- Enhanced maternity and paternity leave.
- Generous pension through Royal London.
- Comprehensive private medical insurance and wellness scheme through Vitality.
- Cycle to work scheme.
- A vibrant social environment and multinational culture.
But that’s not all. Outside of these standard benefits we also offer resources to allow professional growth and wellness initiatives to nurture a healthy mindset:
- Free subscription to the Calm App – the #1 app for sleep, meditation, and relaxation.
- A focus on welfare which is led by our global wellness team, with mental health first aiders globally.
- Access to a variety of diversity and inclusion initiatives and groups.
- Strong recognition and reward programmes – including a peer‑to‑peer recognition platform, quarterly and annual QS Applaud Awards, Connect with your Career annual PD event.
- Support for volunteering and study leave.
- Free subscription to LinkedIn learning – with over 5000 courses and programmes at your fingertips.
- Options to join our outstanding global Mentorship programme.
Like what you’ve heard? Great, apply now! As a candidate, we know the application and interview process can be daunting and so it’s important that you have a great experience with us. Our dedicated Talent Team will work hard to ensure you are fully informed at all stages and you are really excited by this opportunity to do meaningful work in the education space.
QS Quacquarelli Symonds is proud to be a fair and equal organisation where everyone has the same opportunity to achieve their full potential, irrespective of their background or personal attributes. We celebrate our diversity and believe through sharing our experiences we can learn from one another, be stronger together, and enable our business to thrive.
Head of Data Engineering in London employer: Quacquarelli Symonds Limited
Contact Detail:
Quacquarelli Symonds Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Engineering in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, attend meetups, and engage in online forums. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data pipelines and architecture. This will give potential employers a taste of what you can bring to the table, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions, especially around leadership and collaboration, as these are key for a Head of Data Engineering role. We want to see how you can lead a team and drive results!
✨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, it shows you’re genuinely interested in joining QS and being part of our mission to empower others through education.
We think you need these skills to ace Head of Data Engineering in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Head of Data Engineering role. Highlight your experience with data platforms, leadership skills, and any relevant projects that showcase your ability to drive change in data engineering.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background aligns with QS's mission. Don’t forget to mention your experience with AWS, Snowflake, and any orchestration tools you've used.
Showcase Your Leadership Style: As a Head of Data Engineering, your leadership style matters. In your application, share examples of how you've led teams, fostered collaboration, and driven results in previous roles. We want to see how you can inspire others!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way to ensure your application gets the attention it deserves. Plus, you’ll find all the details you need about the role and our company culture there!
How to prepare for a job interview at Quacquarelli Symonds Limited
✨Know Your Data Inside Out
As a Head of Data Engineering, you’ll need to demonstrate your deep understanding of data architectures and platforms like AWS and Snowflake. Brush up on your knowledge of ETL/ELT processes and be ready to discuss how you've implemented scalable data solutions in the past.
✨Showcase Leadership Skills
This role requires strong leadership and team management abilities. Prepare examples of how you've successfully led teams, mentored engineers, and fostered a culture of technical excellence. Be ready to discuss your approach to building high-performance teams and driving collaboration.
✨Communicate Clearly and Strategically
Effective communication is key in this position. Practice articulating complex technical concepts in a way that’s accessible to non-technical stakeholders. Think about how you can convey your vision for the data platform and how it aligns with QS's strategic objectives.
✨Prepare for Problem-Solving Scenarios
Expect to face some wicked problem-solving scenarios during your interview. Be prepared to discuss specific challenges you've encountered in data engineering and how you approached them. Highlight your ability to adapt and innovate in dynamic environments.