Sr. Data Architect

Data Architect Manufacturing Data Warehouse
Top Consulting is seeking a highly skilled Data Architect to lead the design and development of an enterprise data warehouse to support advanced analytics, reporting, and AI-driven decision-making in the manufacturing industry. The Data Architect will be responsible for advising clients on defining the data architecture strategy, building scalable data models, and integrating data from diverse manufacturing systems (MES, ERP, SCADA, IoT).
Responsibilities:
Data Architecture & Strategy
Define the enterprise data architecture framework to support manufacturing operations, supply chain, quality, and production analytics.
Establish data governance, security, and compliance standards.
Data Modeling & Warehousing
Design scalable dimensional and relational data models (star schema, snowflake schema) for manufacturing analytics and business intelligence.
Lead the development of ETL/ELT pipelines to integrate data from MES, ERP, PLM, IoT sensors, and quality systems.
Optimize data storage and query performance for large manufacturing datasets.
Integration & Platforms
Select and implement modern data platforms (e.g., Snowflake, Databricks, Azure Synapse, AWS Redshift, Google BigQuery).
Oversee integration with manufacturing systems (SAP, Oracle, Siemens Teamcenter, Rockwell, etc.).
Mentor data engineers, analysts, and developers in best practices.
Partner with AI/ML teams to ensure the data warehouse supports advanced use cases (predictive maintenance, defect detection, production optimization).
Requirements:
7+ years of experience in data architecture, data engineering, or business intelligence, preferably in the manufacturing sector.
Proven experience designing and deploying data warehouses, data lakes, or lakehouses.
Strong expertise in SQL, ETL/ELT frameworks, and data modeling methodologies.
Hands-on experience with cloud data platforms (Azure, AWS, Google Cloud Platform).
Familiarity with manufacturing systems and Industry 4.0 technologies (IoT, MES, SCADA, ERP).
Strong understanding of data governance, data quality, and security best practices.
Bachelor s or Master s degree in Computer Science, Data Engineering, Information Systems, or related field.
Preferred Skills:
Experience with real-time streaming data (Kafka, Spark, Azure Event Hub, etc.).
Knowledge of master data management (MDM) in manufacturing contexts.
Familiarity with BI and visualization tools (Power BI, Tableau, Qlik).
Exposure to AI/ML pipelines and supporting data science teams.