SC cleared - Azure Data Engineer

Social network you want to login/join with: SC cleared – Azure Data Engineer, slough col-narrow-left Client: Methods Location: slough, United Kingdom Job Category: Other – EU work permit required: Yes col-narrow-right Job Views: 4 Posted: 31.05.2025 Expiry Date: 15.07.2025 col-wide Job Description: Duration: 6 months Daily rate : £495 inside IR35 Location: London, hybrid working. Can be onsite one day a week Methods are seeking a SC cleared Data Engineer in London, responsible for designing, building, and maintaining scalable data pipelines and infrastructure. The ideal candidate will have expertise in Microsoft Fabric, Azure, Python, and C#. Key Responsibilities: – Design, develop, and optimize data pipelines using Microsoft Fabric and Azure services (eg, Azure Data Factory, Azure Synapse Analytics, Azure Databricks). – Build and maintain scalable, high-performance data architectures to support analytics, reporting, and machine learning workloads. – Write clean, efficient, and maintainable code in Python and C# for data processing, transformation, and integration tasks. – Implement data ingestion, ETL/ELT processes, and data warehousing solutions. – Collaborate with data scientists, analysts, and stakeholders to understand data requirements and deliver solutions. – Ensure data quality, security, and compliance with organizational and regulatory standards. – Monitor and troubleshoot data pipelines, optimizing for performance and cost-efficiency. Key Skills: – Proficiency in Microsoft Fabric for data integration, analytics, and orchestration. – Advanced programming skills in Python for data manipulation, scripting, and automation. – Proficiency in C# for developing custom data applications and integrations. Additional Skills: – Experience with SQL and NoSQL databases (eg, Azure Cosmos DB, SQL Server). – Familiarity with data modelling, data warehousing, and lakehouse architectures. – Knowledge of DevOps practices, including CI/CD pipelines and version control (eg, Git). – Understanding of big data technologies (eg, Spark, Hadoop) is a plus. #J-18808-Ljbffr