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Databricks Engineer

Harnham - Data & Analytics Recruitment
Posted 10 hours ago, valid for a month
Location

London, Greater London EC1R 0WX

Salary

£500 - £600 per day

Contract type

Full Time

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

Sonic Summary

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  • This is a 6-month contract position for an Azure Databricks Engineer with a salary range of £500-£600 per day.
  • The role involves developing and optimizing data lakehouse solutions on Azure for a renewable energy firm in London.
  • Candidates should have strong experience with Azure Databricks and a background in Azure Data Factory, with proficiency in Python and advanced SQL.
  • The position requires hands-on experience with big data tools like Spark and Hadoop, as well as familiarity with CI/CD pipelines and Terraform.
  • The company is focused on sustainable innovation and is undergoing a digital transformation to enhance its data-driven operations.

DATABRICKS ENGINEER

6-MONTH CONTRACT

£500-£600 PER DAY

This role offers a great opportunity for an Azure Databricks Engineer to join a renewable energy firm based in London. You'll play a hands-on role in developing and optimising modern data lakehouse solutions on Azure, while supporting critical analytics and data delivery systems. The environment encourages technical ownership, collaboration, and the chance to tackle complex cloud-native engineering challenges.

THE COMPANYThis is a leading organisation within the renewable energy sector, dedicated to sustainable innovation and data-driven operations. The business is undergoing rapid digital transformation, investing in cloud-based technologies to optimise performance, forecasting, and environmental impact. With operations across multiple regions, their data initiatives play a key role in supporting clean energy production, distribution, and strategy.

THE ROLEYou'll join a collaborative engineering team focused on building scalable, secure, and efficient data platforms on Microsoft Azure. Your work will directly support migration initiatives, analytics enablement, and platform reliability. You'll be responsible for data pipeline development, resource deployment, and ongoing optimisation of cloud-native systems.

Your responsibilities will include:

  • Designing and implementing scalable data lakehouse architectures using Databricks on Azure.

  • Building efficient ETL/ELT pipelines for structured and unstructured data.

  • Working with stakeholders to ensure high-quality, accessible data delivery.

  • Optimising SQL workloads and data flows for analytics performance.

  • Automating infrastructure deployment using Terraform and maintaining CI/CD practices.

  • Supporting secure and performant data access via cloud-based networking.

KEY SKILLS AND REQUIREMENTS

  • Strong experience with Azure Databricks in production environments.

  • Background with Azure Data Factory, Azure Functions, and Synapse Analytics.

  • Proficient in Python and advanced SQL, including query tuning and optimisation.

  • Hands-on experience with big data tools such as Spark, Hadoop, and Kafka.

  • Familiarity with CI/CD pipelines, version control, and deployment automation.

  • Experience using Infrastructure as Code tools like Terraform.

  • Solid understanding of Azure-based networking and cloud security principles.

HOW TO APPLYPlease register your interest by sending your CV via the apply link on this page.

Apply now in a few quick clicks

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.