AWS Data Bricks Data Engineer

Job Description

About the Role
We are looking for a Senior Databricks Data Engineer to Data Practice, focused on building scalable, high-performance data platforms using Databricks and modern cloud-native technologies.
This is a data engineering role, centred on data pipeline development, distributed processing, and platform delivery, with limited DevOps or ML lifecycle responsibility.
What You’ll Be Doing
Designing, building, and operating batch and streaming data pipelines on Databricks
Developing scalable data transformations using Spark / ELT patterns
Engineering high-throughput data processing systems for large datasets
Working with cloud-native data platforms (AWS preferred)
Implementing data models, schema design, and optimisation techniques
Ensuring data pipelines are reliable, performant, and production-ready
Applying data quality, validation, and monitoring frameworks
Collaborating with analysts, architects, and ML teams to enable downstream use cases
Required Skills & Experience
What You’ll Bring
5+ years’ experience in handson data engineering roles
Strong programming skills in Python (and/or Java) and advanced SQL
Proven experience building and running data pipelines in production
Solid understanding of distributed systems and scalable data architectures
Handson experience with AWS data services and cloudnative platforms
Experience with Databricks or similar distributed data processing platforms
Familiarity with CI/CD, monitoring, and operational support of data platforms
Solid experience in data modelling and large-scale data system
Nice to Have
Exposure to ML / AI use cases via data platforms
Exposure to modern BI and analytics tooling
Experience working in regulated or securityconscious environments
Consulting or clientfacing delivery experience 

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