Principal Architect, EDT Data Platform Engineering (Hybrid)

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.