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.
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