Data Analyst

FaySan Francisco, CA
9hHybrid

About The Position

As a Data Analyst at Fay, you'll sit in the Strategic Initiatives pod as the strategic partner and analytical engine that powers decision-making across the organization. You're someone who has built data infrastructure at growing companies before; you know what good looks like, and you've seen what breaks at scale. You combine deep technical execution with exceptional business judgment and executive-level communication skills. You excel at translating complex data into clear, compelling insights that drive executive decision-making and company strategy. Whether you're presenting to the C-suite or partnering with product leaders, you know how to distill analysis into actionable narratives that influence direction and accelerate outcomes. You'll be the foundational builder of our data function, establishing the metrics, dashboards, and analytical frameworks that become the single source of truth for teams across the company. This is a role for someone who thrives in 0-to-1 environments, has lived through hypergrowth, and brings both the technical rigor and strategic thinking to build scalable data infrastructure from the ground up. If you're energized by high-impact work, partnering deeply with leadership, and using data to unlock company-wide leverage, this role is for you.

Requirements

  • 7-10 years of experience in Data Analytics, Analytics Engineering, or Business Intelligence in high-growth tech or healthcare environments
  • Proficiency in SQL with the ability to write clean, efficient queries and understand how to optimize, debug, and scale them
  • Proven track record building end-to-end analytics solutions from defining metrics and building pipelines to delivering executive dashboards at companies with rapidly changing data needs
  • Strong analytics engineering fundamentals including data modeling, dimensional design, and building reusable, tested data transformations
  • Experience with modern data transformation and warehousing tools such as dbt, Fivetran, or Snowflake and the ability to debug issues across the pipeline
  • Comfort with ambiguity and the ability to structure complex, open-ended problems into clear analytical frameworks
  • Executive-level communication skills with a proven ability to translate complex data into compelling insights for the C-suite and cross-functional collaboration, influencing strategic decisions through clear storytelling, and tailoring your message to drive action across the company
  • Track record in fast-paced environments with the ability to prioritize, deliver quality work under pressure, and move quickly without sacrificing rigor
  • NYC or SF-based and ready to be in-office on a hybrid schedule to collaborate closely with leadership and develop a deep understanding of the business

Nice To Haves

  • Solid understanding of engineering and development best practices, including clean data modeling, code reviews, testing, and version control
  • Working knowledge of Python for analysis, automation, or light data engineering tasks

Responsibilities

  • Own data and analytics for critical business areas by partnering directly with executives and cross-functional leaders to define metrics, build analytical frameworks, and deliver insights that drive strategic decisions
  • Translate data into executive-ready insights by distilling complex analysis into clear, compelling narratives that influence C-suite decision-making, shape company strategy, and communicate the "so what" with precision and impact
  • Architect the data foundations by designing core KPIs, building self-service analytics infrastructure, and establishing the single source of truth that scales with the business
  • Build production-grade data infrastructure by developing clean, reliable, well-documented pipelines from ingestion to transformation to reporting, following modern data engineering best practices
  • Enable data-driven decision making through intuitive dashboards, self-service capabilities, and tools that give stakeholders fast access to the insights they need
  • Drive impact through storytelling by translating complex analysis into clear narratives, actionable recommendations, and executive-ready insights
  • Improve data quality and governance by partnering with engineering to ensure systems, pipelines, and models are accurate, consistent, and built for scale
  • Surface insights proactively by identifying trends, anomalies, and opportunities before they're asked for, bringing a point of view on what matters most
  • Build a culture of analytics excellence by creating documentation, enablement materials, and training that raise data literacy across the organization
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