Databricks Senior Data Engineer - London (Hybrid) - Up to £85,000

Databricks - Apache Spark - Delta Lake - Python - SQL - Azure

We're partnering with a fast-growing technology business that's investing heavily in its data platform and engineering capability. This is an opportunity to join a highly collaborative team where you'll play a key role in shaping a modern Databricks environment, influencing technical decisions, and delivering scalable data solutions that directly impact the business.

Working within a cloud-first environment, you'll collaborate closely with Data Scientists, Analysts, Product teams, and senior stakeholders to build robust, high-performing data products whilst helping drive engineering best practice across the organisation.

The Role

As a Senior Data Engineer, you'll be responsible for:

• Building and maintaining scalable data pipelines within Databricks.
• Developing and optimising batch and streaming data workflows.
• Designing and implementing Lakehouse architectures and medallion data models.
• Implementing data quality, monitoring, and observability frameworks.
• Maintaining security, governance, and access control standards.
• Collaborating with Data Scientists and Analysts to deliver business-critical data products.
• Driving engineering best practice through code reviews and technical standards.
• Identifying platform optimisation and cloud cost reduction opportunities.
• Translating business requirements into scalable technical solutions.
• Contributing to tooling decisions, documentation, and continuous improvement initiatives.

What's On Offer?

• Salary up to £85,000.
• Hybrid working model.
• Modern Databricks and Azure technology stack.
• Exposure to large-scale, enterprise-level data platforms.
• Opportunity to influence architecture and engineering standards.
• Collaborative and supportive engineering culture.
• Ongoing learning and professional development opportunities.
• Strong career progression within a growing technology business.

Key Experience Required

• Proven experience as a Data Engineer within production environments.
• Strong hands-on experience with Databricks, Apache Spark, Delta Lake, Python, and SQL.
• Experience building and supporting scalable ETL/ELT pipelines.
• Strong understanding of distributed data processing and data modelling.
• Cloud platform experience across Azure, AWS, or GCP.
• Experience implementing data quality frameworks and pipeline monitoring.
• Excellent communication and stakeholder engagement skills.

Desirable Experience

• Databricks certification.
• Unity Catalog and Databricks Asset Bundles.
• Terraform or Bicep.
• dbt or similar transformation frameworks.
• Kafka, Event Hubs, or other streaming technologies.
• Retail, supply chain, or consumer goods industry experience.

Apply Now

This is a fantastic opportunity to join a business that is genuinely investing in modern data technologies and offers the chance to work on complex, large-scale engineering challenges.

Apply today or send your CV directly for immediate consideration.