Data Analyst (Fintech)

TL;DR

Data Analyst (Fintech): Powering strategic decision-making across the organization by translating complex data into clear, compelling insights. Focus on building scalable data infrastructure from the ground up, establishing metrics, dashboards, and analytical frameworks to become the single source of truth.

Location: Must be NYC or SF-based and ready to be in-office on a hybrid schedule

Company

hirify.global's mission is to make nutrition a foundational pillar of preventative care, improving outcomes, accessibility, and affordability at scale by building AI-powered infrastructure to transform preventative healthcare.

What you will do

• Define metrics, build analytical frameworks, and deliver insights that drive strategic decisions by partnering directly with executives and cross-functional leaders.
• Translate data into executive-ready insights by distilling complex analysis into clear, compelling narratives.
• 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.
• Enable data-driven decision making through intuitive dashboards, self-service capabilities, and tools that give stakeholders fast access to the insights they need.
• Improve data quality and governance by partnering with engineering to ensure systems, pipelines, and models are accurate, consistent, and built for scale.

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
• 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 have

• 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

Culture & Benefits

• Move together, work hard, stay energized, and make time to celebrate the wins along the way.
• Committed to creating an inclusive environment for all employees.