The Lead Data Engineer will be responsible for overseeing data engineering projects and ensuring the integrity and efficiency of data pipelines.

Summary of Technical Skills:

• Experienced in leading small to medium technical teams, handling task allocation, technical escalations, and representing the team in Agile ceremonies and client meetings. Strong expertise in designing and implementing logical and physical data models for cloud and hybrid data warehouse environments. Skilled in building data architectures for structured, semi-structured, and unstructured data, with hands-on experience across multiple full lifecycle data warehouse implementations.
• Proficient in data modeling tools such as ER/Studio and ER/Win, with a solid understanding of data integration architectures, data profiling, and creating source-to-target mappings. Adept in provisioning and configuring Microsoft Azure Data Platform services including Azure Data Lake Store, Azure Storage, Azure Synapse, Azure Data Factory, Azure SQL Database, Logic Apps, and APIs.
• Technical strengths include Python, SQL scripting, SQL, and PySpark, with general cloud architecture competency—capable of translating requirements into end-to-end data pipelines. Possesses API knowledge, with a preference for candidates who can develop APIs

Preferred Experience/Skills/Certifications

• Microsoft Fabric
• Microsoft Azure Cosmos DB, Data Flows, Express Route, Azure Active Directory
• Experience creating strategies to migrate customers from on-premise environments to
• Azure
• Power BI and semantic modeling
• AWS Glue & Azure Data Factory
• AWS S3 & Azure Blob
• AWS Athena & Azure Databricks
• AWS Redshift & Azure Synapse
• AWS ECS & Azure AKS