Azure AI Architect

4 days ago


Grand Rapids, MI, United States Apolis Full time
Azure AI Architect
Work site: Grand Rapids (Onsite)


As a Senior Data Architect, you will lead the design and implementation of enterprise-grade data solutions on Microsoft Azure. You will architect scalable data platforms, guide cross-functional teams, and ensure robust data governance and delivery frameworks. Your role will be pivotal in driving modernization, optimizing data flows, and enabling advanced analytics across the organization.

Key Responsibilities

Architect and lead the development of large-scale, cloud-native data platforms using Azure services.
Define and enforce data architecture standards, governance policies, and best practices.
Collaborate with business stakeholders, data scientists, and engineering teams to translate business needs into technical solutions.
Design and implement end-to-end data pipelines for ingestion, transformation, and consumption.
Ensure data quality through cleansing, mapping, and transformation aligned with business rules.
Lead solution design leveraging Azure Data Factory, Synapse, Data Lake, and other services.
Drive automation and DevOps integration for continuous delivery and infrastructure as code.
Oversee data warehousing strategies, including dimensional modeling and OLAP design.
Mentor junior architects and developers, fostering a culture of technical excellence.
Evaluate emerging technologies and recommend strategic adoption.

Required Skills & Experience

10+ years of experience in data architecture, with 6+ years on Azure cloud platforms.
Proven expertise in:
Azure Data Factory, Synapse Analytics, Azure SQL, Data Lake, Logic Apps
SQL (advanced), Spark-SQL, PySpark (preferred)
Dimensional modeling, OLAP, and data warehousing principles
Experience with Microsoft Fabric, Azure Databricks,Unity Catalog.
Strong understanding of data governance, security, and compliance frameworks.
Excellent leadership, communication, and stakeholder management skills.
Ability to strategize and influence data architecture decisions across enterprise programs.

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