Golden Technology
Overview
Business Data Architect Responsibilities
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. Technical Solution Delivery
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. Data Governance & Compliance
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. Stakeholder & Business Engagement
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. Mentorship & Technical Leadership
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. Qualifications
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). Education Requirements
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). Location
Cincinnati, OH Fort Mitchell, KY Salary
$130,000.00-$150,000.00
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Business Data Architect Responsibilities
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. Technical Solution Delivery
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. Data Governance & Compliance
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. Stakeholder & Business Engagement
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. Mentorship & Technical Leadership
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. Qualifications
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). Education Requirements
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). Location
Cincinnati, OH Fort Mitchell, KY Salary
$130,000.00-$150,000.00
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