Analytics Engineer (AI)

TL;DR

Analytics Engineer (AI): Building reliable data pipelines, dbt models, reporting layers, and customer-facing analytics for an enterprise AI platform serving the financial industry with an accent on SQL, data quality, business intelligence, and cross-functional analytics. Focus on designing scalable transformations, integrating financial and GTM data, and turning complex datasets into trusted decisions for Finance, Product, Engineering, and enterprise customers.

Location: On-site in New York City, United States

Salary: $150,000–$230,000 base salary, plus equity and benefits

Company

hirify.global is an early-stage AI product company transforming financial workflows for investment banks, private equity funds, and investment firms.

What you will do

• Build and maintain data pipelines and dbt models that transform raw data into reliable datasets.
• Own reporting layers, internal tooling, dashboards, and customer-facing usage analytics.
• Develop expertise in the data model and provide trusted analysis to stakeholders across Finance, GTM, Product, and Engineering.
• Integrate third-party financial data vendors and support GTM analytics for account health, pipeline reporting, and customer activity.
• Build data infrastructure for FP&A, unit economics, board reporting, and enterprise customer ROI analytics.
• Improve data quality, testing, documentation, and standards across the analytics codebase.

Requirements

• 4–8 years of experience in analytics, data engineering, or a related field.
• Deep SQL proficiency and experience with modern cloud data warehouses, preferably Snowflake.
• Hands-on experience with dbt models, tests, and macros.
• Experience building useful dashboards and reports with Sigma, Looker, Hex, or similar tools.
• Full-stack mindset, strong business judgment, and ability to connect data work to business outcomes.
• Ability to work across multiple stakeholders and business domains independently.

Nice to have

• Experience with financial or B2B data vendors such as LSEG, FactSet, Crunchbase, ZoomInfo, or Apollo.
• Familiarity with Salesforce data models and GTM data pipelines.
• Python proficiency for data transformation or analytical work.
• Background in financial services, enterprise SaaS, vertical AI, or early-stage startup analytics.

Culture & Benefits

• Ownership, autonomy, and comfort working through ambiguity.
• Collaborative, thoughtful, organized, and high-accountability environment.
• Opportunity to work at the frontier of AI and financial technology.
• Equity for full-time employees.
• Comprehensive medical, dental, and vision coverage, plus paid time off.