Senior Data Engineer designing and delivering scalable data pipelines at QS. Implementing data solutions to empower higher education analytics and insights.
QS
Hybrid Senior Data Engineer – 12-month contract
Posted 1 hour ago
About the role
- Senior Data Engineer at QS specializing in designing and building high‑quality data assets. Working in a hybrid model, effectively contributing to international higher education analytics.
Responsibilities
- Design, build, and maintain high‑quality data assets by combining and harmonising third‑party datasets, proprietary QS data, scraped collections, and internal data sources
- Develop, optimise, and maintain dbt models, tests, and documentation to ensure transparency, reproducibility, and engineering excellence
- Partner closely with the Data Lead to ensure: comprehensive data lineage from raw ingestion through to final assets, robust source‑level and transformation‑level data quality checks, consistent metadata capture and governance
- Apply advanced data modelling techniques to unify heterogeneous data into coherent, scalable structures that support ranking methodologies, research insights, and analytics
- Profile and validate source datasets, conducting thorough statistical, structural, and semantic checks before asset integration
- Build and maintain standardised transformation frameworks that improve trust, comparability, and traceability across QS’s data assets
- Collaborate with the wider Data Engineering team to ensure alignment with platform standards, transformation principles, and shared engineering practices
- Support data scientists, analysts, and BI teams by delivering well‑documented, dependable data assets that meet evolving analytical needs
- Uphold rigorous data governance by embedding validation and documentation throughout workflows
- Document data models, transformation logic, and operational procedures clearly and consistently
- Mentor team members in dbt, modelling, asset development, and best practices in data quality and lineage
Requirements
- Significant hands‑on experience designing, building, and maintaining dbt transformation pipelines
- Proven capability in developing data assets that integrate heterogeneous sources including third‑party datasets, scraped data, and proprietary internal systems
- Strong proficiency in SQL and Python, particularly for data shaping, ingestion orchestration, and quality automation
- Practical experience working with cloud data platforms such as Snowflake, BigQuery, or equivalent
- Deep understanding of data lineage, metadata management, governance, and reproducible modelling practices
- Experience with data profiling, anomaly detection, schema validation, and quality assurance frameworks
- Strong collaborative skills, especially in cross‑functional environments involving acquisition, sourcing, and analytics teams
- Experience with data scraping pipelines or public‑data ecosystems
- Familiarity with modelling datasets used for rankings, research, or analytical subscription products
- Experience in higher education technology is appreciated but not required
Benefits
- Competitive base salary
- Access to an annual bonus scheme (for qualifying roles only)
- 20 days annual leave, plus public holidays
- Generous maternity and paternity leave
- Access to an Employee Assistance Programme (EAP) and MiCare health
- A vibrant social environment and multicultural and multinational culture
- Free subscription to the Calm App – the #1 app for sleep, meditation, and relaxation
- Access to a variety of diversity and inclusion initiatives and groups
- Strong recognition and reward programs – 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
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