Senior Azure Data Engineer (Databricks)

About the role

Senior Azure Data Engineer (Databricks)

Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent

Engineer advanced data solutions at scale in a world-class consulting environment.

The Role

As a Senior Azure Data Engineer (Databricks) at Capco, you will play a hands-on role in designing, building, and deploying scalable and secure data engineering pipelines using the Databricks platform on Azure. You'll partner with clients to understand their data needs and develop innovative solutions that drive business transformation. You'll also contribute to engineering best practices and continuous improvement across cross-functional teams. Databricks platform on Azure. You'll embrace AI-enabled ways of working, using approved AI and automation tools where appropriate to improve engineering productivity, accelerate delivery, and enhance solution quality while applying sound engineering judgement and responsible AI practices.

What You'll Do

- Design and develop robust data pipelines using Delta Lake, Spark Structured Streaming, Unity Catalog, and Azure-native services.

- Build real-time, event-driven solutions using technologies such as Kafka and Azure Event Hubs, applying AI-enabled engineering approaches where appropriate to improve delivery efficiency.

- Develop and maintain CI/CD pipelines using Azure DevOps, Jenkins, GitHub Actions, and modern DevOps practices to support reliable deployments.

- Collaborate with clients and multidisciplinary teams to translate business requirements into scalable, production-ready data solutions.

- Champion clean code, data lifecycle optimisation, engineering best practices, and the responsible use of approved AI tools and automation to improve collaboration and delivery.

What We're Looking For

- Proven hands-on experience with the Databricks platform, including orchestration and enterprise-scale Azure data engineering solutions.

- Strong technical skills in Python, PySpark, and SQL, with experience working with distributed data processing frameworks.

- Expertise delivering end-to-end data pipelines across ingestion, transformation, and serving layers within modern Data Lakehouse architectures.

- Experience with schema design, GDPR-compliant data solutions, DevOps tooling, and CI/CD processes.

- A collaborative approach to engineering with experience using AI-enabled tools responsibly to improve productivity while maintaining appropriate human oversight, governance, and solution quality.

Bonus Points For

- Development experience using Scala or Java.

- Familiarity with Cloudera, Hadoop, Hive, Spark, and related distributed data ecosystems.

- Experience working with sensitive data and applying data privacy regulations, including GDPR.

- Curiosity to explore new technologies, including responsible AI and automation, to continuously improve engineering practices.