Senior Data Engineer

Required Qualifications

• A bachelor's degree in computer science, information technology, software engineering, or a related field is required, although relevant experience may substitute.
• Five or more years of experience with enterprise data pipelines, analytical models, and application integrations are required.
• Production experience with cloud ingestion, transformation, dimensional modeling, data quality, monitoring, troubleshooting, and curated data delivery is required.
• Advanced SQL and proficiency with Python and PySpark are required.
• Git-based source control, CI/CD, automated deployment, and environment configuration experience are required.

Preferred Qualifications

• Hands-on experience with Azure Databricks, Delta Lake, Unity Catalog, Databricks Workflows, Auto Loader, Lakeflow Declarative Pipelines, or comparable tooling is preferred.
• Experience with MuleSoft Anypoint Platform or another enterprise integration platform and Power BI datasets or semantic models is preferred.
• Experience integrating operational systems such as ERP, CRM, finance, logistics, WMS, or manufacturing systems is preferred.

Skills and Abilities

• Understand lakehouse and medallion architecture with bronze, silver, and gold layers.
• Use batch, streaming, incremental, change-data-capture, API-based, and file-based ingestion patterns.
• Design dimensional models and curated data products for reporting, self-service analytics, machine learning, and AI.
• Trace discrepancies across source systems, transformations, integrations, and reporting layers.
• Balance speed with maintainability, scalability, security, governance, reliability, and cost.
• Communicate clearly, document technical designs, and collaborate across technical and non-technical teams.
• Apply secure cloud-data practices such as access control, secrets management, encryption, service principals, and environment separation.

About the Company