Data Engineer
Hands-on Data Engineer building and maintaining Cognita's modern data platform: designing scalable, resilient pipelines in Azure Databricks (bronze/silver medallion layers) from CRM, MIS, Finance and HR sources, with strong data quality, monitoring, schema management and CI/CD. Hybrid role: 4 days in London office, 1 day from home.
- Compensation
- Not disclosed
- Location
- London, United Kingdom
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Proven experience designing and delivering production-grade data pipelines in modern cloud environments
- Strong expertise in Azure Databricks, including PySpark, Delta Lake and Databricks Jobs
- Excellent SQL skills
- Solid understanding of medallion architecture principles
- Experience working with data from CRM, MIS, Finance and HR systems
- Experience building scalable ingestion frameworks using APIs and structured/semi-structured formats (JSON, CSV, Parquet)
- Ability to implement data quality controls and manage schema changes
- Experience using Git-based version control to support engineering practices
- Collaborative approach and problem-solving; translate business requirements into reliable technical solutions and work with technical and non-technical stakeholders
Nice to have
- Degree in Computer Science, Data Engineering, Information Systems or related field
- Azure certifications and ongoing professional development in cloud data technologies
Full description
About Cognita:
Cognita is a global leader in independent education. Founded in 2004, we are a growing community of 90 schools in 20 countries - in Europe, North America, Latin America, Asia and the Middle East - serving more than 100,000 students. Each of our schools are proudly unique, however our collective purpose is to create an environment where everyone can, "Thrive in a rapidly evolving world".
About the Role:
The Data Engineer will play a key role in building and maintaining Cognita’s modern data platform, developing robust and scalable data pipelines within our Azure Databricks environment. Working with data from a range of core systems, including HubSpot CRM, MIS, Finance and HR platforms, you will design, develop and optimise end-to-end data solutions that transform raw information into reliable, high-quality datasets for business use. Responsible for managing data across the bronze and silver layers of our medallion architecture, you will implement effective ingestion processes for structured and semi-structured data, ensure pipelines are resilient, observable and well-governed, and support evolving business requirements through strong data quality, monitoring and schema management practices. Collaborating closely with analysts, analytics engineers, platform engineers and the wider Group Data team, you will help deliver data models that meet organisational needs while maintaining high engineering standards through documentation, code reviews and CI/CD practices. This is an excellent opportunity for a hands‑on Data Engineer who enjoys solving complex data challenges, working within a modern cloud-based technology stack, and translating business requirements into scalable and maintainable data solutions.
Working Arrangement: 4 days per week in London office, 1 day working from home.
To view the role profile, click here
Who We Are Looking For:
We are looking for a skilled and hands‑on Data Engineer with proven experience designing and delivering production‑grade data pipelines within modern cloud environments. You will have strong expertise in Azure Databricks, including PySpark, Delta Lake and Databricks Jobs, alongside excellent SQL skills and a solid understanding of medallion architecture principles. Comfortable working with data from CRM, MIS, Finance and HR systems, you will have experience building scalable ingestion frameworks using APIs and a range of structured and semi‑structured data formats, including JSON, CSV and Parquet. You will be confident implementing data quality controls, managing schema changes, and using Git‑based version control to support robust engineering practices. With a collaborative approach and strong problem‑solving skills, you will be able to translate business requirements into reliable technical solutions and work effectively with both technical and non‑technical stakeholders. A degree in Computer Science, Data Engineering, Information Systems or a related field, along with Azure certifications and ongoing professional development in cloud data technologies, would be advantageous.