Principal 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 stakeho