Data Engineer

• Taking ownership of existing pipeline workloads to ensure stability and continuity.
• Building, maintaining, and optimizing standard ETL/ELT processes and workflow orchestrations.
• Working heavily with Databricks, Azure Data Factory, and AWS to move and transform data.
• Collaborating daily with offshore team members in India, ensuring smooth handovers and shared engineering goals during your standard UK working hours.
• Writing clean, scalable Python code and utilizing Git for version control and CI/CD best practices.

The Opportunity We are partnering with a leading enterprise organization to find a Mid-Level Data Engineer for an immediate-start contract. We are looking for a reliable, hands-on engineer to jump straight in and support critical, existing data pipelines., The Must-Have Technical Stack To hit the ground running, you will need 3 to 5 years of commercial Data Engineering experience, along with hands-on expertise in the following:

• Databricks & Delta Lake: Strong PySpark/SQL skills for data transformation and lakehouse management.
• Cloud Orchestration: Extensive experience with Azure Data Factory (ADF) and a solid working knowledge of AWS (e.g., S3).
• Event Streaming: Practical experience with Kafka for real-time/streaming data workloads.
• Core Engineering: Deep proficiency in Python and standard ETL process engineering.
• Version Control: Comfortable using Git within a collaborative team environment.