Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. 

Job Summary

We’re seeking a seasoned Senior Staff Analyst of Primary Customer Research and Field Intelligence to lead our customer insight and Field Intelligence initiatives and shape how we understand and act on customer needs. This leader will design and execute research programs that directly influence our product, marketing, and customer experience strategies. The ideal candidate combines deep research expertise with business acumen and storytelling skill.

The role requires active collaboration with the team in California, USA, and calls for a global operating mindset—one that embraces adaptable work hours as an opportunity to connect, contribute, and drive meaningful impact across time zones.

This role resides within Equinix’s Enterprise Data & Analytics team, and reports to the Senior Director of Data Product, Go-To-Market.

Responsibilities

• Lead the design and execution of primary research programs, including quantitative surveys, qualitative interviews, ethnographies, and concept testing

• Translate complex customer insights into clear, actionable recommendations that guide strategic decisions across product, marketing, and CX teams

• Oversee the research roadmap and manage partnerships with external research vendors and agencies

• Champion customer-centricity across the organization by embedding research insights into planning and go-to-market processes

• Manage and mentor a team of researchers, ensuring best practices in methodology, analysis, and stakeholder communication

• Work cross-functionally with analytics, data science, and UX research to integrate multiple data sources for a holistic view of the customer

• Present executive-level insights that inform C-suite priorities, market positioning, and innovation strategy

Partner with Go-To-Market and engineering teams as a peer

• Work side-by-side with Go-To-Market, Engineering, AI and data science leadership to evaluate technical options, identify technical tradeoffs, estimate effort, and make architecture recommendations where applicable

• Critique and challenge inflated estimates and oversimplified proposals; know when a "simple" request is actually complex

• Guide engineering toward pragmatic solutions when requirements are ambiguous or shifting

Drive business impact through stakeholder partnership

• Build trust-based relationships with senior business stakeholders by understanding their strategy, pain points, and how data and AI solutions can help

• Run monthly/quarterly portfolio reviews to ensure delivery stays on track and aligned to business needs

• Set clear expectations, push back on low-value requests, and educate stakeholders on what's possible and what's not

• Frame ambiguous problems, generate hypotheses, and drive to recommendations when there's no clear precedent

Manage through transition and complexity

• Lead data product continuity during a major technology stack migration; ensure critical reporting capabilities remain intact as systems transition over multiple quarters

• Partner with engineering to design interim solutions that bridge old and new data models during migration

• Balance strategic roadmap work with operational needs; protect time for building while keeping the lights on for products in ‘maintenance’ mode

Bring outside-in perspective

• Stay current on analytics, AI/ML, and data product trends; bring relevant innovations (e.g., Product 360 approaches, AI-augmented BI, knowledge graphs) to inform roadmap decisions

• Serve as a trusted advisor to business partners on what's emerging and what's hype

Qualifications

Required

• Bachelor’s degree in Marketing, Business, Behavioral Science, or related field; advanced degree preferred

• 1-3+ years of experience in customer insights, market research, or related fields, with at least 5 years in a leadership capacity

• Proven success in designing and implementing large-scale primary research studies

• Expertise in both qualitative and quantitative methods and in synthesizing research into business impact

• Strong data storytelling and communication skills, including executive presentation experience

• Experience with tools such as Qualtrics, Medallia, SPSS, or similar research platforms

• Excellent leadership, collaboration, and vendor management abilities

Preferred / Nice to have:

• Experience managing AI/ML product development end-to-end, from problem framing through deployment and iteration

• Experience building customer-facing data products, not just internal tools / dashboards

• Experience with building LLM ready semantic layer – ensure semantic layer is governed, well-modeled, and reliable 

• Cloud data platform expertise (e.g., BigQuery, Snowflake, Databricks, Redshift)

• Familiarity with MLOps concepts: feature stores, model serving, monitoring, retraining

• Industry background in cloud infrastructure, B2B SaaS, data centers, telecommunications, or multi-cloud networking

Skills:

• Able to break down ambiguous, cross-functional problems and drive to a solution when there's no clear precedent or playbook

• Comfortable reading and critiquing customer research artifacts – customer data models, survey designs - and asking the right questions when something doesn't add up

• Able to quickly T-shirt size level of effort for data and AI initiatives across product and engineering

• Able to effectively translate between engineering and business - simplifying technical tradeoffs for executives while maintaining credibility with engineers

• Drives decisions forward; knows when to build consensus and when to make the call and move on

• Takes ownership of outcomes, not just delivery; holds themselves and partners accountable to business impact