Director, Business Intelligence & Data Analytics

Staar Surgical Company•Lake Forest, CA

2d•$170,000 - $245,000

About The Position

The Director of Business Intelligence & Data Analytics is responsible for leading STAAR Surgical's enterprise BI and Data Analytics organization, including the strategy, architecture, and delivery of modern cloud-based data platforms. This role partners closely with FP&A, Sales & Marketing, Supply Chain, Operations, Quality, Regulatory, and Information Technology leadership to define, implement, and support scalable data and analytics solutions, including advanced AI-enabled capabilities, across the enterprise. This role additionally supports data governance, data engineering, and AI/analytics innovation initiatives. The position partners closely with business stakeholders and IT leadership to strengthen data architecture, integration pipelines, self-service analytics adoption, and supports the deployment of AI solutions including conversational (chat) and agentic AI capabilities across the organization.

Requirements

Bachelor's degree in Information Technology, Computer Science, Data Analytics, or related discipline required Or equivalent combination of education/experience.
Undergraduate degree and 10+ years relevant experience, or Graduate degree and 8+ years relevant experience.
10+ years of experience in Business Intelligence, Data Analytics, Data Engineering, or related data management disciplines.
5+ years of leadership experience managing BI, data analytics, or data engineering teams.
Direct, hands-on experience implementing and administering Snowflake as an enterprise cloud data warehouse.
Direct, hands-on experience implementing and managing Fivetran or similar automated ELT/ETL data integration pipelines.
Demonstrated experience implementing AI solutions, including conversational (chat-based) AI assistants and agentic AI workflows, within business or analytics environments.
Experience integrating BI and analytics platforms with Oracle Fusion ERP, Salesforce CRM, Quality, HR Systems, etc.
Experience with cloud data warehouse and visualization platforms such as Power BI, Tableau, Azure, or AWS Redshift.
Experience with data privacy and security considerations in a regulated environment.
Experience operating within Agile or hybrid SDLC environments.
Ability to partner effectively with FP&A, Sales & Marketing, Supply Chain, Operations, Quality, Regulatory, IT, and executive leadership.
Demonstrated leadership driving modernization, innovation, and operational maturity initiatives, particularly around cloud data platforms and AI adoption.
Excellent facilitation and communication skills, with the ability to adapt to the level and nature of the audience.
Ability to translate business goals and objectives into data, analytics, and AI roadmap aligned with enterprise strategy.
Deep technical knowledge of Oracle Fusion ERP, Oracle EPM, and Salesforce.com CRM platform architectures, underlying data models, and integration/extraction methods (e.g., REST/SOAP APIs, OData, OTBI, BI Publisher (BIP),BICC, database views) required to reliably extract and integrate data into enterprise reporting and analytics solutions.
Expert-level proficiency in Snowflake, encompassing enterprise architecture design, data engineering and pipeline development, and the ongoing build, optimization, and support of production Snowflake solutions — including performance tuning, security/access governance, and cost management.
Knowledge of Fivetran (or equivalent) connector-based data integration and ELT pipeline design.
Able to apply data governance, data architecture, metadata management, and data quality management practices.
Ability to define KPI Governance – Enterprise KPI definitions, Executive Scorecards, Master KPI Catalog, Common dimensions
Advanced understanding of data warehouse design principles, data shaping techniques, and structured/unstructured data for analysis.
Strong knowledge of AI/ML and generative AI concepts, including large language models, conversational AI/chatbots, Retrieval-Augmented Generation Architecture, Prompt Engineering and integrating Agents with tools and enterprise applications and Agentic AI Frameworks and Orchestration.
Strong understanding of data privacy, data security, and general IT control processes such as segregation of duties, access, backup and recovery, and disaster recovery.
Expert knowledge of and ability to apply commonly used SDLC methodologies (Waterfall, Agile, etc.).
Excellent analytical, organizational, communication, and leadership skills.

Nice To Haves

Relevant certifications in cloud data platforms (e.g., Snowflake SnowPro), data engineering, or AI/ML are a plus.
Experience leading data governance, data quality, and data architecture modernization initiatives strongly preferred.
Ability to communicate in Japanese and/or Mandarin is a plus.

Responsibilities

Lead and manage global Business Intelligence and Data Analytics teams supporting enterprise reporting, self-service analytics, and advanced analytics initiatives.
Define and operationalize STAAR Surgical's enterprise data strategy, including data architecture, data governance, data engineering, and analytics delivery roadmaps.
Drive the modernization of STAAR's data platform leveraging Snowflake as the enterprise cloud data warehouse and Fivetran for automated, scalable data integration and ELT pipelines.
Establish scalable data governance and delivery frameworks supporting Agile and modern Software Development Lifecycle (SDLC) processes across BI and analytics initiatives.
Lead BI and analytics oversight for integrations with ERP, MES, CRM, eQMS, HCM, Industrial IoT, and other enterprise and manufacturing data sources.
Define, implement, and support best-fit BI and analytics solutions for FP&A, Sales & Marketing, Supply Chain, Operations, Quality, and Regulatory departments.
Lead the identification, evaluation, and implementation of AI solutions, including conversational (chat-based) AI and agentic AI capabilities, to automate business processes, augment decision-making, and enhance self-service analytics.
Partner with Software Engineering, IT, Data Security, and business stakeholders to ensure responsible, secure, and compliant deployment of AI/ML and generative AI capabilities within analytics and reporting solutions.
Ensure data pipelines, warehousing, and visualization solutions (Snowflake, Fivetran, Power BI, Tableau, Azure, or similar) are scalable, reliable, and aligned with enterprise data quality standards.
Oversee data governance policies and procedures pertaining to critical business data, data architecture, data modeling, metadata management, and data engineering standards.
Effectively manage delivery of new BI, analytics, and AI technologies through proper SDLC policies, procedures, and change management practices.
Provide ongoing monitoring, support, and maintenance for implemented BI, analytics, and AI solutions.
Support inspections/audits related to data privacy, data security, and data integrity in a regulated environment.
Provide leadership and mentorship to data warehouse architects, developers, analysts, administrators, and cross-functional teams.
Establish standardized data governance frameworks, templates, procedures, and delivery models supporting global operations.
Manage the hiring, staffing, and development of a diverse and effective BI, analytics, and data engineering workforce.
Responsible for career development/planning, performance, and pay discussions of team members.
Influence individuals within and outside the IT department to drive adoption of data-driven and AI-enabled decision-making.
Prepare and present reports and roadmaps to all levels of leadership and staff, including business cases for AI and analytics investments.
Establish and maintain budgets, operational plans, and performance requirements for the BI and Data Analytics function.
Utilize best practice processes around work assignments, project management, and quality of output while maximizing overall team performance.
Build relationships with business customers to improve services and ensure service levels are being met.
Other duties as assigned.