Head of Data Engineering

Join to apply for the Head of Data Engineering role at QS Quacquarelli Symonds

Join to apply for the Head of Data Engineering role at QS Quacquarelli Symonds

Role:
Head of Data Engineering

Location: UK, London

Job type:
Full time, Permanent – Hybrid

We work on an 8‑hour workday. Two days in the office each week; the rest remote.

Why QS?

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.

At QS, you’ll be responsible for implementing real change in the international higher education landscape. You’ll take on meaningful challenges that see a positive impact across the business and the wider sector.

We’re confident you’ll feel right at home here. QS was named as one of Newsweek’s Top 100 Most Loved Workplaces® in the UK (October 2023), recognising the respect, trust and appreciation that drive our culture every day. And as a gold‑accredited Investors in People organisation – putting us among the top 28% of workplaces globally – it’s official: QS is a place where everyone can thrive.

As a Head of Data Engineering, this is what you’ll be doing:

At QS, we believe that empowering people through data drives meaningful impact in higher education worldwide. 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. You 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.

This is an exciting opportunity to shape the future of higher education and workforce development by joining a dynamic Data Engineering team. If you are passionate about leading, innovating, and making a tangible difference in a diverse and supportive environment, we invite you to envision yourself in this impactful role at QS.

• 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.
• 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.

• 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…