Senior Data Engineer (Microsoft Azure Data & AI)

Location: Remote, Austin, TX, United States

Salary: $155,000–$175,000 per year

Company

hirify.global delivers Microsoft, Azure, Power Platform, data, AI, and customer experience solutions for clients through its global digital practice.

What you will do

• Design and build end-to-end Azure data platforms covering ingestion, cleaning, transformation, analytics, and activation.
• Architect Medallion lakehouse patterns with Microsoft Fabric, OneLake, Delta Lake, Azure Databricks, PySpark, Python, and SQL.
• Own dimensional, normalized, and semantic data modeling for trustworthy and reusable analytics-ready data.
• Build batch and streaming pipelines, APIs, data services, and MCP integrations for business systems, Data Agents, and agentic AI interfaces.
• Implement governance, access control, metadata, and lineage using Microsoft Purview and/or Unity Catalog.
• Mentor engineers, review technical designs, support production operations, and advise client stakeholders on architecture decisions.

Requirements

• 5–8 years of data engineering experience with ownership of production Azure data pipelines.
• Expert proficiency in Python, SQL, and PySpark for distributed data pipelines.
• Hands-on experience with Azure Data Factory, Microsoft Fabric, Synapse, ADLS Gen2, Azure Databricks, Delta Lake, OneLake, and Medallion architectures.
• Experience with data modeling, enterprise data architecture, APIs, MCP integrations, orchestration, and CI/CD.
• Knowledge of Microsoft Purview and/or Unity Catalog, data governance, and security tooling.
• Bachelor’s or master’s degree in a relevant technical discipline, strong problem-solving skills, and the ability to lead client-facing technical discussions.

Nice to have

• Microsoft certifications such as Azure Data Engineer Associate or Fabric Analytics Engineer Associate.
• Databricks certifications.

Culture & Benefits

• Remote work arrangement.
• Work within a Microsoft Partner Practice of more than 100 experts.
• Opportunities to contribute to reusable engineering frameworks, accelerators, and standards.
• Work on complex digital solutions focused on customer experience.