Azure Data Engineer
Job title:
Azure Data support Engineer
Will the role be 100% remote, hybrid or 100% office?
Hybrid (3 Days Week)
If the role is hybrid/ office based specify location:
Coventry, UK
Duration of assignment:
06 Months
Role description:
Non-negotiable technical requirements:
- Strong Azure Synapse engineering
- Strong PySpark development
- Azure SQL DB stabilisation including SQL performance tuning
Seniority signals:
- Proven independent operator
- Able to deliver at pace with minimal oversight
- Can diagnose and permanently fix BAU issues rather than relying on repeated manual intervention
Please provide candidate mappings against:
- specific Synapse/PySpark examples owned through production support
- SQL performance tuning examples
- evidence of independent delivery.
Key responsibilities:
- Non-negotiable technical requirements:
- Strong Azure Synapse engineering
- Strong PySpark development
- Azure SQL DB stabilisation including SQL performance tuning
- Seniority signals:
- Proven independent operator
- Able to deliver at pace with minimal oversight
- Can diagnose and permanently fix BAU issues rather than relying on repeated manual intervention
- Please provide candidate mappings against:
- specific Synapse/PySpark examples owned through production support
- SQL performance tuning examples
- evidence of independent delivery.
Key skills/knowledge/experience:
- BSc minimum, MSc or PhD in a STEM field (e.g., Computer Science, ,
- 10+ years of professional experience in data Engineer or a related field, with a proven track record of delivering impactful solutions.
- SQL Pools, serverless SQL, Spark Pools
- Strong SQL, performance tuning, query optimization
- Data modeling & warehouse concepts (Kimball/Inmon)
- Pipelines, triggers, linked services, integration runtime
- Data flows & orchestration of large-scale ETL/ELT workloads
- Distributed data processing, partitioning strategies, Spark optimization
- Data transformations, Delta Lake, and notebook-based development
- Hierarchical namespace, folder structure design, ACLs, RBAC
- Working with large-scale datasets and optimized storage formats
- Strong understanding of ETL/ELT frameworks, data lifecycle, and data architecture.
- Experience with Azure DevOps, CI/CD, Git branching strategies.
- Proficiency in SQL and Python.
- Knowledge of Databricks (added advantage).
- Experience in Agile/Scrum environments.
- Excellent problem-solving, communication, and documentation skills.
Good to Have
- Domain knowledge. Understanding of the water industry.
Person specification:
- Collaborate with customers and stakeholders.
- Grow your career, while being exposed to new technologies.
- Lead projects and inspire both colleagues and stakeholders.
- Mentor junior employees using your expertise