As a Principal Architect, EDT Data Platform Engineering you will translate enterprise data architecture into scalable engineering solutions on the Azure and Databricks Lakehouse platform. You will partner with delivery teams, business representatives, and data stewards to build governed data pipelines, analytics-ready models, and reusable automation that improves consistency across projects and teams.

What you will do:

Technical Responsibilities:

• Build and maintain ingestion frameworks using Azure Data Factory, Databricks, and Spark.
• Implement Bronze-to-Silver transformations with data quality checks, schema validation, and data contract rules.
• Optimize batch and streaming pipelines for performance and cost.
• Own CI/CD pipelines in Azure DevOps and automate project onboarding, including repositories, pipelines, policies, and templates.
• Maintain Infrastructure as Code and automation using Terraform, PowerShell, and Python; troubleshoot pipeline failures and permission issues.
• Design curated Gold-layer data models, including star and snowflake schemas, fact tables, dimensions, surrogate keys, and slowly changing dimensions.
• Align reusable models, KPI definitions, and business logic with the enterprise semantic layer in Power BI, Microsoft Fabric, and downstream tools.
• Manage model changes through impact analysis, backward compatibility, regression support, and documented column derivation logic.
• Implement Unity Catalog standards, naming conventions, metadata policies, data quality frameworks, and role- and attribute-based access controls.
• Translate high-level architecture into low-level designs, reusable templates, and engineering playbooks.

Leadership & People Management Responsibilities:

• Guide delivery teams through onboarding, debugging, and design reviews.
• Create reusable assets and hands-on guidance that build engineering capability and reduce repeat questions.

Knowledge and Capabilities:

• Assess complex data systems, identify patterns, and recommend practical solutions.
• Explain technical concepts clearly to technical and non-technical stakeholders.
• Partner with business representatives and data stewards to define requirements, validate metrics and edge cases, and guide solution decisions.
• Identify opportunities for process optimization, redesign, and new or updated policies.

What You Need:

Required Qualifications

• Bachelor's degree from an accredited university in Computer Science, Engineering, Information Systems, Business, or an equivalent field of study.
• Minimum 8 years of experience in data engineering, data warehousing, and data and analytics platforms, including recent hands-on delivery on Azure and Databricks Lakehouse platforms.
• Experience with Azure Data Factory, Azure Data Lake Storage, Azure SQL, Databricks Delta Live Tables, Delta Lake, Spark, Workflows, and Unity Catalog.
• Advanced experience with PySpark or Python and SQL, including batch and streaming pipeline design.
• Experience with Azure DevOps pipelines, repositories, and policies; PowerShell automation; CI/CD; and Infrastructure as Code.
• Experience with schema enforcement, data contracts, data quality frameworks, metadata-driven design, monitoring, debugging, and performance tuning.

Preferred Qualifications

• Master's degree in Management Information Systems, Business Administration, or a related discipline, or an Azure analytics certification.
• Experience with Microsoft Fabric
• Experience within the medical device or another regulated industry.

United States of America Pay Ranges:

• USN: $135,600 - $225,900 USD Annual
• US10: $149,200 - $248,500 USD Annuall
• US20: $162,700 - $271,100 USD Annual

View the U.S. work location and transparency guide to find the pay range for your location.