Senior Data Engineer - Azure & ML-Ready Analytics

Hunter Bond; Greater London; Hybrid; GBP 85,000 - 120,000; Full time

Benefits offered by this job

Tech Upgrade Stipend

Learning & Development Budget

Quarterly Innovation Days

Adventure Days

Gym access & wellness

Flexible working options

Job summary

Hunter Bond partners with a fast-growing technology company to hire a Data Engineer / Database Developer. You will design, build and optimise scalable Azure-based databases while contributing to ML data pipelines in Python.

This role covers the full data lifecycle—from architecture and performance tuning to enabling analytics and ML use cases. You will collaborate with engineers, data scientists and stakeholders in a dynamic, hyper-growth environment with learning budgets and stipends.

Qualifications

• 5+ years in data engineering or database development roles.
• Experience with Microsoft Azure data services including Azure SQL, Data Factory, Synapse or similar.
• Proficiency in Python for data processing and ML workflows.

Responsibilities

• Design and build SQL databases from scratch with scalability and performance in mind.
• Architect, implement, and manage cloud-based databases in Azure.
• Develop and maintain data pipelines to support analytics and ML workloads.
• Collaborate with data scientists to prepare data for ML modelling.
• Contribute to Python-based ML models and data processing workflows.
• Ensure data governance, security, and integrity.

Skills

SQL & DB design

Azure data services

Python data processing

ETL processes

Data modelling

Distributed data systems

ML frameworks

CI/CD

Big data tools

Data governance

Tools

Azure Data Factory

Synapse

Job description

Hunter Bond partners with a fast-growing technology company to hire a Data Engineer / Database Developer. You will design, build and optimise scalable Azure-based databases while contributing to ML data pipelines in Python.

This role covers the full data lifecycle—from architecture and performance tuning to enabling analytics and ML use cases. You will collaborate with engineers, data scientists and stakeholders in a dynamic, hyper-growth environment with learning budgets and stipends.