Solutions Engineer, Data Engineering

What you'll do

• Design and implement data ingestion, transformation, and integration pipelines using Azure Data Factory, Synapse, and Microsoft Fabric.
• Build and optimize scalable data lakehouse and warehouse solutions while ensuring security and cost effectiveness.
• Develop and maintain data models, ETL/ELT processes, and historical versioning for multi-source datasets.
• Manage Azure Data Lake Storage Gen2 environments including data organization, lifecycle management, and archival strategies.
• Implement data validation, cleansing, and quality controls to ensure auditable and trusted data platforms.
• Apply security best practices such as encryption and identity-based access control for regulated industries like HIPAA and NIST.
• Produce high-quality technical documentation including design artifacts, migration plans, and operational runbooks.
• Execute modern engineering practices including source control, CI/CD pipelines, and automated monitoring for production environments.

What we're looking for

• Proven hands-on experience delivering modern data engineering solutions on Microsoft Azure and/or Microsoft Fabric.
• Strong foundation in data pipelines, Lakehouse architectures, and platforms like Azure Data Factory, Synapse, Databricks, and SQL Server.
• Experience designing and operating production data platforms including modeling, incremental processing, and monitoring.
• Solid understanding of data security, governance, and compliance for sensitive or regulated data.
• Familiarity with modern engineering practices such as source control, CI/CD, and infrastructure as code.
• Ability to translate business requirements into technical solutions in consulting or project-based environments.
• Microsoft Certified Azure Data Engineer Associate certification is required or expected within six to twelve months.
• Preferred certifications include Microsoft Certified Fabric Analytics Engineer Associate or Azure Solutions Architect Expert.