Head of Data Engineering in London

Location: UK, London. Job type: Full time, Permanent – Hybrid. 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.

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.

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-proof 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 optimize data delivery and performance.
• Master's degree of 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. Are you ready to shape the future of higher education?

We take investing in our people very seriously.

Equal opportunities: 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.