
Business Data Architect
- Barnes, WI
- Permanent
- Full-time
- Develop and own the enterprise data architecture strategy, ensuring alignment with manufacturing business goals and IT roadmap.
- Define architecture standards, patterns, and best practices for data ingestion, integration, storage, and analytics.
- Lead the design of high-performance data environments that integrate ERP, MES, PLM, supply chain, and quality management systems.
- Oversee the design and implementation of enterprise data platforms, including data lakes, warehouses, and real-time streaming solutions.
- Ensure architectural consistency across data engineering, analytics, and AI/ML initiatives.
- Lead data platform selection and optimization (e.g., Databricks, Snowflake, Microsoft Fabric, AWS/Azure/GCP-based solutions).
- Partner with data engineering teams to build robust ETL/ELT pipelines supporting structured, semi-structured, and unstructured data.
- Collaborate with the Data Governance team to ensure metadata management, lineage tracking, and data quality frameworks are integrated into the architecture.
- Ensure compliance with manufacturing industry regulations (ITAR, AS9100, ISO 9001, GDPR, CCPA) and corporate security standards.
- Translate complex technical concepts into clear business language for executives and functional leaders.
- Collaborate with operations, engineering, supply chain, finance, and commercial teams to define data requirements that drive process optimization and decision-making.
- Stay ahead of trends in data architecture, cloud-native manufacturing solutions, IIoT (Industrial Internet of Things), and AI/ML.
- Recommend adoption of new tools and technologies that enhance manufacturing analytics and predictive capabilities.
- Provide guidance to data architects, engineers, and analysts on best practices in modern data architecture.
- Conduct architecture reviews and ensure solutions meet both business and technical objectives.
- Excellent verbal and written communication skills; able to influence at all organizational levels.
- Strong project leadership and organizational skills, managing multiple high-impact initiatives simultaneously.
- Ability to balance strategic vision with tactical execution.
- Deep expertise in data modeling (conceptual, logical, physical) and database technologies (SQL, NoSQL).
- Hands-on experience with modern data platforms (Databricks, Snowflake, AWS Redshift, Azure Synapse, Google BigQuery).
- Data platform engineering, Terraform, CI/CD.
- Familiarity with ERP (SAP, Oracle), MES, PLM, and quality systems data integration.
- Experience with streaming data architectures (Kafka, Spark Streaming) and IIoT platforms.
- Proficiency in data transformation languages and frameworks (SQL, Python, Spark, dbt).
- Bachelor’s degree in computer science, Information Systems, Engineering, or related field; Master’s preferred.
- 15+ years of experience in data architecture and engineering, with at least 3 years in manufacturing or related industrial environments.
- Proven experience delivering enterprise-scale data solutions, integrating operational technology (OT) with information technology (IT).