Job Description

• Help to architect and scale enterprise cloud data warehouses to deliver immediate data accessibility across business units.
• Design, construct, and automate robust data pipelines for large-scale data ingestion, cleansing, and cross-platform integration.
• Transform raw data science and AI prototypes into production-ready, highly reliable machine learning models.
• Maximize system efficiency by performance-tuning data integration pipelines and analytical queries.
• Build custom, automated health-monitoring and anomaly-detection tools to safeguard pipeline integrity and enterprise data quality.

• Extensive experience designing modern data lakehouses and schemas utilizing the Microsoft SQL Server ecosystem.
• Advanced proficiency orchestrating enterprise data movement and workflows using Azure Data Factory.
• Hands-on expertise using Databricks and Spark to process, manipulate, and optimize massive, complex datasets.
• Strong background writing clean, production-grade Python or modern scripting languages to handle automation and data transformations.
• Deep understanding of cloud storage architectures, relational database mechanics, and continuous integration/continuous deployment (CI/CD) pipelines.