Quick Overview
Job Description
Job Description
We are seeking an experienced Azure Data Architect with strong expertise in Master Data Management (MDM), ETL/ELT, and enterprise data architecture to design and lead scalable data solutions on Microsoft Azure. The ideal candidate will have deep hands-on experience with Azure Data Factory, Databricks, Synapse Analytics, data warehousing, data lakes, data governance, and MDM implementations.
Key Responsibilities
- Design and architect enterprise-scale MDM, ETL/ELT, data warehouse, and data lake solutions on Azure.
- Define enterprise data integration strategies and architecture patterns using Azure Data Factory, Databricks, and Synapse Analytics.
- Lead Master Data Management (MDM) initiatives, including master data modeling, data quality, reference data, governance, and stewardship.
- Design scalable and optimized data warehouses, data lakes, lakehouse, and analytical platforms.
- Architect integrations across diverse source systems, including ERP, CRM, APIs, databases, and third-party applications.
- Establish standards and best practices for data modeling, metadata management, master data, data lineage, and data governance.
- Develop and enforce architectural patterns for batch and real-time data integration.
- Drive performance tuning, scalability, security, availability, and reliability of Azure data platforms.
- Evaluate existing data platforms and recommend modernization and optimization strategies.
- Collaborate with business stakeholders, data engineers, application teams, analytics teams, and enterprise architects to define data architecture roadmaps.
- Translate business and technical requirements into scalable, secure, and maintainable data architectures.
- Define data architecture standards, design principles, reusable frameworks, and governance processes.
- Provide architectural oversight and technical governance across multiple data projects.
- Mentor data engineers and technical teams and provide guidance on architecture, design, and implementation.
- Ensure solutions follow Azure security, compliance, governance, and enterprise architecture standards.
Required Skills
- 10+ years of experience in data architecture, data engineering, or enterprise data platforms.
- Strong expertise in Microsoft Azure data services.
- Hands-on experience with:
- Azure Data Factory (ADF)
- Azure Databricks
- Azure Synapse Analytics
- Azure Data Lake Storage (ADLS)
- Strong experience designing ETL/ELT frameworks and data integration pipelines.
- Proven experience with Master Data Management (MDM) and reference data management.
- Strong understanding of data governance, data quality, metadata, lineage, and stewardship.
- Strong knowledge of data modeling, including conceptual, logical, and physical data models.
- Experience designing data warehouses, data lakes, and lakehouse architectures.
- Strong SQL skills and experience with relational and cloud databases.
- Experience integrating data from ERP, CRM, APIs, and third-party systems.
- Strong understanding of enterprise data architecture patterns and best practices.
- Experience with performance optimization, security, scalability, and high availability of data platforms.
- Strong communication and stakeholder-management skills.
Preferred Qualifications
- Experience with MDM platforms such as Informatica MDM, Microsoft Purview, Reltio, or similar technologies.
- Experience with Azure Purview / Microsoft Purview for data catalog, governance, and lineage.
- Knowledge of Power BI and modern analytics architectures.
- Experience with streaming/event-driven data architectures such as Kafka or Azure Event Hubs.
- Experience with CI/CD, DevOps, and Infrastructure as Code for Azure data platforms.
- Azure certifications such as Azure Solutions Architect Expert or Azure Data Engineer Associate are a plus.
Ideal Candidate
The ideal candidate is an enterprise-level Azure Data Architect, not simply an Azure Data Engineer. They should be able to define the architecture, make technology/design decisions, establish MDM and governance standards, and provide technical leadership while still understanding the underlying Azure data technologies deeply.
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