Data Platform Engineer (Analytics & Modelling)
Role details
Job location
Tech stack
Job description
We are looking for a platform-oriented Data Scientist who is as comfortable working with data pipelines and data models as they are with analysis.
This is not a pure modelling role. You will focus on designing and enabling data science and analytics workloads on modern data platforms, ensuring that data is accessible, reliable, and production-ready for downstream use.
You will play a key role in shaping how data is structured, governed, and consumed across enterprise environments., We offer a range of tailored benefits that support your physical, emotional, and financial wellbeing. Our Learning and Development team ensure that there are continuous growth and development opportunities for our people. We also offer the opportunity to have flexible work options., We are an equal opportunities employer. We believe in the fair treatment of all our employees and commit to promoting equity and diversity in our employment practices. We are also a proud Disability Confident Committed Employer - we are committed to creating a diverse and inclusive workforce. We actively collaborate with individuals who have disabilities and long-term health conditions which have an effect on their ability to do normal daily activities, ensuring that barriers are eliminated when it comes to employment opportunities. In line with our commitment, we guarantee an interview to applicants who declare to us, during the application process, that they have a disability and meet the minimum requirements for the role. If you require any reasonable adjustments during the recruitment process, please let us know. Join us in building a truly diverse and empowered team.
Requirements
- 3-6 years' experience in data-focused roles (data science, analytics engineering, or data platform roles)
- Strong hands-on experience with at least one of Snowflake, Databricks and Microsoft Fabric
- Advanced SQL skills and experience working with large-scale, distributed datasets
- Strong Python skills for data processing, transformation, and analysis
- Solid understanding of:
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Data modelling (dimensional, Lakehouse, etc.)
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Data warehousing concepts
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Batch and/or streaming data pipelines
- Experience working in cloud environments
- Experience collaborating with data engineers, architects, and platform teams
- Ability to deliver production-ready data assets, not just exploratory outputs
Preferred skills and qualifications
- Familiarity with Spark and distributed data processing frameworks
- Experience with performance tuning and cost optimisation on cloud data platforms
- Exposure to data governance frameworks and tooling
- Experience supporting BI and analytics tools (Power BI, Tableau, Qlik)
- Basic understanding of machine learning workflows (as a secondary capability, not core focus)
Key competencies
- Platform-first mindset: thinks in terms of systems, scalability, and reuse
- Strong data modelling capability: able to design data structures that support multiple use cases
- Operational focus: builds solutions that are reliable, maintainable, and production-ready
- Collaboration: works effectively across engineering, analytics, and business teams
- Clear communication: able to translate complex data concepts into business-relevant language
- Pragmatic delivery: balances technical quality with real-world constraints