Contract: 6 to 12 months (negotiable based on project scope)
Working Model Hybrid: 3 days onsite | 2 days remote per week
Purpose
Our client is seeking experienced Data Engineers to design, build, and maintain scalable enterprise data pipelines and platform components. The successful candidates will play a key role in delivering trusted, high-quality data that supports analytics, AI, and business intelligence across the organisation.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Build and optimise enterprise data integrations and data platform components.
- Ensure data quality, reliability, and performance across data pipelines.
- Develop data solutions that support analytics, AI, and reporting workloads.
- Collaborate with Data Architects, Product Owners, and Analytics teams.
- Optimise data processing, scalability, and platform performance.
- Implement engineering best practices, testing, and automation.
- Support the continuous improvement of the enterprise data platform.
Requirements
- 5+ years' experience in Data Engineering.
- Strong proficiency in Python and SQL.
- Experience with Apache Spark.
- Hands-on experience with Microsoft Fabric.
- Experience with Databricks, Snowflake, and Denodo.
- Experience with Azure Synapse Analytics.
- Experience with Azure Data Factory is preferred.
- Strong understanding of ETL/ELT pipeline development.
- Experience working with Azure Cloud Data Platforms.
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