Director, Data, Programs & Strategic Initiatives

Ayar Labs•San Jose, CA

1d•Onsite

About The Position

Ayar Labs is shattering AI data bottlenecks by moving data at the speed of light. As pioneers of co-packaged optics (CPO), we are using light instead of electricity to move data faster, further, and with a fraction of the energy needed to fuel the explosive growth of AI models. Backed by industry giants like NVIDIA, AMD and Intel and manufactured in partnership with the world’s leading semiconductor ecosystem, Ayar Labs’ co-packaged optics solution is key to unleashing next-generation AI scale-up architectures. Reporting to the Chief Information Officer, the Director of Data, Programs & Strategic Initiatives sets the strategy and operating model for Ayar Labs' enterprise data capabilities. This leader is accountable for trusted data across the semiconductor product lifecycle—from design and validation through test, manufacturing, supply chain, quality, and customer delivery—and for turning that data into reliable decisions, scalable platforms, and measurable business outcomes. The Director leads and develops the Data Pillars team, establishes governance and architecture standards, manages the portfolio and operating cadence, and resolves the company's most complex cross-functional data challenges. Success requires both executive-level leadership and enough technical depth to challenge assumptions, diagnose root causes, and earn credibility with engineering teams, foundries, OSATs, suppliers, and business partners.

Requirements

Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience; advanced degree preferred.
12+ years of progressive experience in data engineering, analytics, data architecture, enterprise data management, or related disciplines, including 5+ years leading technical teams and managers.
A minimum of 5 years of direct, recent experience in the semiconductor industry is required. Candidates must understand the design-to-manufacturing lifecycle and have worked with one or more relevant domains such as silicon design or verification data, product and test engineering, characterization, yield, wafer fabrication, assembly and packaging, quality and reliability, or semiconductor supply-chain data.
Demonstrated success hiring, coaching, organizing, and developing high-performing technical teams while setting direction, accountability, and succession plans.
Proven ownership of enterprise data strategy and modern data platforms, including data warehouses or lakehouses, ELT/ETL pipelines, data modeling, APIs, metadata, master/reference data, observability, and platform reliability.
Experience establishing data ownership, stewardship, lineage, metric definitions, validation controls, access standards, and issue-resolution mechanisms in a complex technical environment.
Strong working knowledge of SQL, Python or comparable data tooling, BI and visualization platforms, statistical analysis, and cloud data technologies; able to review architectures and challenge technical decisions without needing to be the primary implementer.
Demonstrated ability to prioritize investments, manage roadmaps and resources, reduce technical debt, track delivery and risk, and drive multiple complex initiatives from strategy through sustained operations.
Executive-level written and verbal communication with the ability to build trust, explain complex data issues clearly, and align engineering, operations, suppliers, and business leaders around decisions.

Nice To Haves

Experience with silicon photonics, advanced packaging or chiplets, foundry and OSAT data exchange, manufacturing/test/yield analytics, or engineering-focused AI/ML solutions is strongly preferred.

Responsibilities

Set the Enterprise Data Strategy: Define and execute a multi-year data and analytics roadmap aligned to company priorities, semiconductor product milestones, operational scale, and business growth.
Lead and Develop the Data Organization: Build, coach, and retain a high-performing team spanning data architecture, engineering, analytics, governance, and program leadership; establish clear ownership, performance expectations, and development plans.
Create Trusted Semiconductor Data: Establish governance, stewardship, metadata, lineage, quality controls, and common definitions for semiconductor design, characterization, test, yield, manufacturing, supplier, and quality data.
Scale the Data Platform: Oversee secure, reliable, and cost-effective data platforms, pipelines, models, and analytics products that support operational reporting, engineering insight, AI/ML use cases, and executive decision-making.
Drive Cross-Functional Outcomes: Partner with engineering, product, operations, quality, IT, finance, and external manufacturing partners to translate ambiguous business and technical problems into prioritized, durable data solutions.
Resolve the Hardest Problems: Lead root-cause analysis and corrective action for persistent data-quality disputes, gaps in genealogy and traceability, inconsistent metrics, supplier-data failures, and other issues that cross organizational boundaries.
Own Portfolio Governance and Operating Cadence: Run quarterly planning, weekly execution reviews, resource and dependency management, risk escalation, and outcome reporting for the Data Pillars portfolio.
Advise Executive Leadership: Provide the CIO and leadership team with clear recommendations, tradeoffs, performance measures, and early warning on data, delivery, organizational, and supplier risks.