The Senior Data Engineer will be responsible for designing and implementing data solutions that support business objectives.

Technical Summary:

• Highly skilled in designing and implementing logical and physical data models for both cloud and hybrid data warehouse environments.
• Experienced in building data architectures that support structured, semi-structured, and unstructured data, with multiple full lifecycle data warehouse implementations.
• Strong understanding of data integration architectures, data profiling, and creating source-to-target mappings.
• Proficient in data modeling tools such as ER/Studio and ER/Win, and capable of 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. Demonstrates the ability to quickly adopt new technologies.
• Technical expertise includes Python, SQL scripting, SQL, and PySpark, with solid cloud architecture competency—able to convert requirements into end-to-end data pipelines.
• Has required API knowledge, with added value for candidates who can create APIs.

Preferred Capabilities:

• Hands-on experience or familiarity with Microsoft Fabric, Azure Cosmos DB, Data Flows, ExpressRoute, and Azure Active Directory.
• Knowledgeable in migration strategies from on-premise to Azure.
• Additional strengths include Power BI with semantic modeling, AWS Glue and Azure Data Factory, AWS S3 and Azure Blob, AWS Athena and Azure Databricks, AWS Redshift and Azure Synapse, plus container-orchestration experience via AWS ECS and Azure AKS.