Data Architect
We are seeking an experienced Data Architect to lead the design and implementation of modern data solutions across our enterprise data ecosystem — including lakehouses, data warehouses, data marts, and operational data stores using the Microsoft Azure and Fabric stack. A key focus will be leading the migration and modernization of legacy ETL solutions to Microsoft Fabric.
Key Responsibilities:
Architecture & Design
- Design end-to-end enterprise data solutions using Azure Data Lake Storage Gen2, Synapse Analytics, Azure SQL Database, Data Factory, and Microsoft Fabric
- Develop data architecture blueprints for delta lakes, Fabric Lakehouse, and data warehouse environments
- Define data warehouse and data mart architectures using Kimball dimensional modeling and Data Vault methodologies
- Architect medallion architecture (Bronze/Silver/Gold) for lakehouse implementations
- Establish data governance frameworks — lineage, metadata management, and data quality standards
- Create reusable reference architectures and design patterns
Migration & Modernization
- Lead assessment and inventory of existing legacy ETL assets (mappings, workflows, sessions, parameters)
- Develop migration roadmap with phased approach for transitioning to Microsoft Fabric
- Create transformation logic equivalency matrices between legacy and Fabric components
- Design metadata-driven automation frameworks to accelerate migration
- Establish testing and validation strategies to ensure data integrity post-migration
- Identify re-engineering and optimization opportunities beyond lift-and-shift
- Manage parallel run strategies and scheduling transitions during cutover
Technical Implementation
- Lead implementation of ETL/ELT pipelines using ADF, Synapse Pipelines, Databricks, and Fabric Data Pipelines
- Design data ingestion frameworks for batch, streaming, and real-time processing
- Develop transformation frameworks using T-SQL, Spark SQL, PySpark, and Fabric Dataflows Gen2
- Implement CDC patterns for incremental data loading
- Design partitioning, indexing, and optimization strategies for performance tuning
Leadership & Collaboration
- Define standards and best practices for data engineering on Azure and Fabric
- Drive adoption of DataOps and CI/CD practices for data pipelines
- Lead proof-of-concepts and technical evaluations for new data technologies
- Mentor data engineers and junior architects
- Partner with business stakeholders, BI teams, and DevOps for delivery alignment
- Produce technical documentation — architecture diagrams, data flows, migration plans, and design specs
Technical Skills:
Microsoft Azure & Fabric
- Azure Data Factory, Synapse Analytics, ADLS Gen2, Azure SQL Database, Azure Databricks
- Microsoft Fabric — Lakehouse, Data Warehouse, Data Factory, Dataflows Gen2, Real-Time Intelligence
- OneLake, Shortcuts, and Direct Lake mode
Data Architecture & Modeling
- Expert in dimensional modeling, Data Vault 2.0, and normalized modeling
- Delta Lake, Apache Spark, and lakehouse architectures
- MPP databases — Synapse Dedicated SQL Pools, Fabric Data Warehouse
Programming
- Strong T-SQL — complex queries, stored procedures, performance tuning
- Python/PySpark for data transformation and processing
DevOps & Governance
- Azure DevOps, Git, CI/CD for data solutions
- Azure Purview / Fabric Data Catalog, metadata management
- Security frameworks — encryption, RBAC, compliance (GDPR, HIPAA, SOC2)
Qualifications
Experience:
- 8–12 years in data engineering, data warehousing, and analytics
- 2+ years architecting solutions on Microsoft Azure data platform
- Proven experience leading migration projects from legacy ETL tools to cloud platforms
- Track record of delivering enterprise-scale data solutions
- Bachelor's or Master's degree in Computer Science, Information Systems, or related field
Certifications (Preferred):
- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Certified: Azure Data Engineer Associate (DP-203)
- Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)