Principal Data/Business Intelligence Engineer

Primary Duties & Responsibilities Lead the architecture, design, and evolution of enterprise-scale data warehouse and analytics platforms supporting global business operations and strategic decision-making. Define and implement enterprise data modeling standards, governance practices, and scalable architectural frameworks for analytics and reporting solutions. Design and optimize Snowflake-based solutions, including advanced SQL development, dbt frameworks, JavaScript-based stored procedures, and data pipelines. Lead the development of scalable and maintainable dimensional data models, including staging, intermediate, semantic, and enterprise reporting layers with automated testing, lineage tracking, and documentation standards. Drive enterprise data integration initiatives involving Oracle E-Business Suite (EBS), ERP systems, manufacturing systems, external APIs, and cloud-based data platforms. Serve as the technical authority for enterprise BI and analytics engineering solutions, providing guidance and mentorship to engineers and cross-functional technical teams. Partner with business leaders and stakeholders across Finance, Supply Chain, Manufacturing, Operations, and IT to translate strategic business objectives into scalable technical solutions. Lead architecture reviews, performance optimization efforts, data quality initiatives, and enterprise scalability planning for mission-critical analytics systems. Establish best practices for ETL/ELT development, CI/CD deployment processes, code quality, testing frameworks, and operational support procedures. Evaluate emerging technologies and recommend improvements to enterprise data architecture, analytics platforms, and reporting capabilities. Lead complex cross-functional programs and coordinate technical activities across multiple teams to ensure successful delivery of enterprise initiatives. Drive continuous improvement initiatives for data governance, metadata management, reliability, observability, and operational excellence. Participate in strategic planning discussions related to enterprise analytics capabilities, data modernization efforts, and long-term platform roadmaps. Education & Experience Minimum 9+ years of experience in enterprise data engineering, BI engineering, analytics engineering, or related disciplines. Minimum 8+ years of hands‑on experience with Oracle E-Business Suite (EBS), enterprise data warehousing, and Snowflake development. Deep expertise in enterprise data architecture, dimensional modeling, data warehouse design, and large-scale analytical systems. Advanced proficiency in SQL, PL/SQL, SnowSQL, T‑SQL, and performance optimization techniques for large-scale data platforms. Extensive experience designing and developing advanced stored procedures, orchestration frameworks, and scalable ELT/ETL pipelines. Strong experience building enterprise-grade Snowflake data warehouse solutions using dbt with automated testing, lineage tracking, CI/CD integration, and engineering best practices. Extensive experience with enterprise data integration tools and platforms such as SAP Data Services, SSIS, Informatica, Snowflake Openflow, Airflow, or Azure Data Factory. Strong understanding of enterprise business processes within high‑tech manufacturing environments, including Finance, Supply Chain, Manufacturing, and Operations. Strong expertise in Oracle ERP functional modules and Oracle EBS technical architecture, including schema design, interfaces, and data structures. Proven ability to lead complex technical initiatives and influence architectural direction across multiple organizations. Demonstrated experience mentoring engineers and providing technical leadership within enterprise engineering teams. Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or related field. Skills Strong analytical and problem‑solving capabilities Self‑motivated and able to work independently in a fast‑paced environment Excellent collaboration and communication skills Detail‑oriented with a focus on quality and reliability Experience with Python for data ingestion, API integration, and automation Familiarity with workflow orchestration tools (Airflow, Azure Data Factory) Experience with BI tools such as Power BI, Tableau, or similar platforms Working Conditions Hybrid work environment with collaboration across cross‑functional teams Fast‑paced, project‑driven workload with multiple concurrent priorities Regular interaction with business stakeholders, data engineers, and leadership teams Primarily computer‑based work involving data analysis, dashboard development, and reporting Participation in meetings, project planning sessions, and operational support activities Standard business hours with occasional flexibility needed to support project deadlines and deliverables Physical Requirements Prolonged periods of sitting and working on a computer Frequent use of hands and fingers for typing and data analysis tasks Ability to communicate effectively verbally and in writing Ability to view and interpret detailed data on computer screens for extended periods Occasionally move or lift office materials and equipment up to 15 pounds Ability to participate in virtual and in‑person meetings and presentations Safety Requirements All employees are required to follow the site EHS procedures and Coherent Corp. Corporate EHS standards. Quality and Environmental Responsibilities Depending on location, this position may be responsible for the execution and maintenance of the ISO 9000, 9001, 14001 and/or other applicable standards that may apply to the relevant roles and responsibilities within the Quality Management System and Environmental Management System. Coherent Corp. is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. #J-18808-Ljbffr II-VI UK, Ltd.