Data Architect - Manufacturing

ABOUT THE ROLE

We are looking for an experienced Senior Data Architect with strong expertise in Microsoft Fabric, enterprise data warehousing, and manufacturing data models. The role requires hands-on technical expertise, architectural leadership, and the ability to design scalable data platforms supporting enterprise analytics and manufacturing operations. The candidate should be comfortable engaging with senior stakeholders, translating business requirements into technical solutions, and guiding implementation teams.

KEY RESPONSIBILITIES

1. Enterprise Data Architecture: Design scalable Enterprise Data Warehouse and Lakehouse solutions, primarily using Microsoft Fabric.

2. Microsoft Fabric: Architect and implement solutions using OneLake, Lakehouse, Data Warehouse, Data Factory Pipelines, Dataflows Gen2, Fabric Notebooks, and Spark.

3. Data Modeling: Develop conceptual, logical, and physical data models, including dimensional modeling, star/snowflake schemas, fact and dimension tables, and SCD.

4. Manufacturing Domain: Design data models supporting production planning, manufacturing operations, inventory, procurement, supply chain, and operational KPIs.

5. Data Engineering: Design and optimize ETL/ELT pipelines using SQL, Python, PySpark, Delta Lake, and relevant orchestration frameworks.

6. Enterprise Integration: Architect data integration with SAP ECC/S/4HANA, ERP systems, databases, APIs, and external data sources, including batch, incremental, and CDC processing.

7. Performance & Cost Optimization: Optimize Spark workloads, SQL queries, storage, compute utilization, and data processing performance.

8. Governance & Security: Establish data quality, lineage, RBAC, security, and governance practices using Microsoft Purview and platform-native capabilities.

9. DevOps & Automation: Define CI/CD, deployment automation, testing, and version control practices using Azure DevOps, GitHub Actions, Git, and Terraform.

10. Architecture Leadership: Lead solution design, technical reviews, architecture governance, and engineering teams.

11. Stakeholder Engagement: Conduct technical workshops, present architecture recommendations, and engage with customers and senior stakeholders.

12. Solution Consulting: Support technical discovery, architecture assessments, solution estimation, and proposal development.

QUALIFICATIONS AND TECHNICAL SKILLS

MUST-HAVE

• 14+ years of experience in Data Architecture, Data Engineering, or Enterprise Data Warehousing.
• Strong hands-on experience with Microsoft Fabric, including OneLake, Lakehouse, Data Warehouse, Data Factory Pipelines, Dataflows Gen2, Notebooks, and Spark.
• Expertise in enterprise data modeling, dimensional modeling, star/snowflake schemas, SCD, and Medallion Architecture.
• Strong proficiency in SQL, Python, PySpark, and Delta Lake.
• Experience designing ETL/ELT pipelines, orchestration workflows, and enterprise data integrations.
• Experience with Microsoft Azure data services, including ADLS Gen2, Azure Data Factory, and Azure SQL.
• Understanding of data governance, security, lineage, data quality, and performance optimization.
• Experience with CI/CD, Git, Azure DevOps, and deployment automation.
• Ability to independently design enterprise data platforms and lead technical implementation.
• Strong customer-facing communication, solution presentation, and stakeholder management skills.

MANUFACTURING DOMAIN - MANDATORY

• Proven experience designing data platforms or enterprise data warehouses for manufacturing organizations.
• Understanding of manufacturing operations, production planning, procurement, inventory, and supply chain processes.
• Experience modeling manufacturing entities such as Product, Material, Plant, BOM, Production Order, Inventory, and Supplier.
• Familiarity with manufacturing KPIs, including OEE, production efficiency, yield, scrap, downtime, and inventory turnover.
• Ability to translate manufacturing business requirements into enterprise data models and analytical solutions.