Domain Delivery Lead- Healthcare

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Azure Architect – Domain Lead (Healthcare)

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.

Please visit Fractal | Intelligence for Imagination for more information about Fractal.

Role Overview

We are seeking an experienced Azure Architect with strong Healthcare domain expertise and deep knowledge of Data Engineering, Azure cloud technologies, and Data Quality (DQ) frameworks. The ideal candidate will lead the design and implementation of scalable, secure, and compliant healthcare data platforms on Microsoft Azure.

This role requires strong expertise in Azure Data Engineering, Databricks, SQL, stakeholder management, and healthcare data ecosystems including regulatory and compliance considerations.

The candidate will work closely with business stakeholders, healthcare SMEs, analytics teams, architects, and engineering teams to drive enterprise-scale cloud data transformation initiatives.

Key Responsibilities

Azure Data Architecture

• Design enterprise-scale healthcare data platforms on Microsoft Azure.
• Architect scalable, secure, and high-performing cloud-native data solutions.
• Define end-to-end architecture for ingestion, transformation, storage, governance, and analytics.
• Lead modernization and migration of legacy healthcare data systems to Azure.
• Ensure architecture aligns with healthcare compliance and governance standards.

Data Engineering & Databricks

• Design and implement large-scale ETL/ELT pipelines.
• Build batch and real-time data processing solutions using Azure Databricks.
• Develop scalable data ingestion frameworks for structured and unstructured healthcare data.
• Optimize performance and scalability of Azure data platforms.
• Implement Lakehouse/Data Lake architectures using Azure services.

Data Quality & Governance

• Define and implement enterprise Data Quality (DQ) frameworks.
• Establish DQ controls for completeness, consistency, accuracy, timeliness, and reconciliation.
• Build automated validation and monitoring mechanisms.
• Enable data lineage, metadata management, and governance practices.
• Collaborate with governance teams to improve data reliability and trust.

Healthcare Domain Responsibilities

• Work with healthcare stakeholders to understand clinical, operational, and analytical data requirements.
• Support healthcare data integration initiatives involving EMR/EHR systems, claims, patient, provider, and operational data.
• Ensure compliance with healthcare regulations and data privacy standards.
• Support healthcare analytics, reporting, and interoperability initiatives.

Stakeholder Management

• Collaborate with business leaders, product owners, architects, and engineering teams.
• Translate business requirements into scalable technical solutions.
• Lead client discussions, architecture reviews, and technical workshops.
• Provide technical leadership and mentoring to engineering teams.
• Manage communication with cross-functional stakeholders and leadership.

Required Skills & Experience

Core Technical Skills

Azure Technologies

Strong hands-on expertise in:

• Azure Data Factory (ADF)
• Azure Databricks
• Azure Synapse Analytics
• Azure Data Lake Storage (ADLS)
• Azure SQL Database
• Azure Functions
• Azure DevOps
• Azure Monitor
• Microsoft Purview / Azure Purview

Data Engineering

• Strong expertise in SQL and Python/PySpark.
• Experience building enterprise-grade ETL/ELT pipelines.
• Strong understanding of data modeling and distributed data processing.
• Experience with Delta Lake and Lakehouse architectures.
• Knowledge of batch and streaming data processing.

Data Quality

• Experience implementing enterprise Data Quality frameworks.
• Stron