Data Architect

We are seeking a highly experienced Data Architect to lead the design and implementation of enterprise-scale data solutions for industrial, manufacturing, and Consumer Packaged Goods (CPG) environments. This role requires strong expertise in data modeling, particularly Kimball Dimensional Modeling, data warehousing, and modern cloud-based data platforms.

Roles & Responsibilities:

• Design and implement scalable enterprise data architectures to support business intelligence, analytics, and operational reporting.
• Lead the development of Kimball dimensional models, including star schemas, fact tables, dimension tables, and Slowly Changing Dimensions (SCDs).
• Create and maintain conceptual, logical, and physical data models using industry-standard data modeling tools.
• Collaborate with Data Analysts, Data Engineers, Data Governance teams, and business stakeholders to translate business requirements into robust data solutions.
• Architect and optimize data pipelines for efficient data ingestion, integration, transformation, and storage.
• Ensure data models align with enterprise data governance, quality, security, and compliance standards.
• Support real-time and historical analytics by designing scalable and high-performance data warehouse solutions.
• Drive best practices in data architecture, metadata management, master data management (MDM), and data lifecycle management.
• Integrate data from multiple enterprise and operational systems, including manufacturing, engineering, ERP, and external platforms.
• Enable advanced analytics, AI/ML initiatives, and GenAI use cases through well-structured and governed data foundations.

Technical requirement:

• Strong expertise in Kimball Dimensional Modeling, Dimensional Data Modeling, Star & Snowflake Schemas, Fact & Dimension Tables, SCD, Data Warehouse Design, Data Vault Modeling, and Enterprise Data Modeling.
• Experience creating Conceptual, Logical, and Physical Data Models using industry-standard methodologies.
• Hands-on experience with ER/Studio, Erwin Data Modeler, PowerDesigner, or similar data modeling tools.
• Strong knowledge of Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage (ADLS), and Data Lakehouse Architectures.
• Experience designing and optimizing ETL/ELT pipelines, data integration solutions, and data orchestration workflows.
• Proficiency in SQL and Python for data transformation, automation, and analytics.
• Experience integrating data using REST APIs and implementing scalable data ingestion frameworks.