Analytics Engineer (New Grad)

PermitFlow
New York City, NYPosted 11 March 2026

Job Description

Analytics Engineer (New Grad) PermitFlow is redefining how America builds. We’re an applied AI company serving the nation’s builders, tackling one of the largest information challenges in the economy: understanding what can be built, where, and how. Our AI agent workforce helps the fastest-growing construction companies navigate everything from permitting and licensing to inspections and project closeouts – accelerating housing, clean-energy, and infrastructure development across the country. Despite being a $1.6T industry, construction still suffers from massive delays, wasted capital, and lost opportunity. PermitFlow has already delivered unprecedented speed, accuracy, and visibility to over $20B in development, helping contractors reduce compliance time, de-risk projects, and scale with confidence. As the U.S. enters a new capex supercycle across data centers, factories, housing, and renewables, joining PermitFlow means building the AI infrastructure at the core of every construction project driving the next wave of reindustrialization. We’ve raised over $90M, most recently completing our Series B, https://www.permitflow.com/blog/permitflow-series-b from top-tier investors including Accel, Kleiner Perkins https://www.linkedin.com/feed/update/urn:li:activity:7401703305569275904/, Initialized, Y Combinator, Felicis, and Altos Ventures, with backing from leaders at OpenAI, Google, Procore, ServiceTitan, Zillow, PlanGrid, and Uber. Our HQ is in New York City with a hybrid schedule (3 in-office days per week). We prefer NYC-based candidates or those open to relocation. ROLE OVERVIEW We are looking for a motivated and curious New Grad Analytics Engineer to join our team. In this role, you will be hands-on designing, building, and maintaining data infrastructure to support scalable and actionable business intelligence. You’ll grow your skills by working directly with senior analytics staff, engineers, product teams, and stakeholders to ensure data integrity, optimize analytics processes, and support decision-making across the company. WHAT YOU'LL DO - Partner with senior staff to implement scalable data models optimized for analytics and company-wide reporting, continuously refining them to meet evolving business needs. - Build and maintain efficient data pipelines to transform datasets for analytics. - Collaborate with product and engineering teams to integrate data from sources like PermitFlow’s CRM, 3rd party vendors, and other internal sources while optimizing for performance and reliability. - Support data quality and governance efforts by helping to define key metrics, track data lineage, and enforce data quality checks. - Deliver analytics solutions, build dashboards, and support teams in using data effectively. - Contribute to maintaining and improving PermitFlow’s data stack to enable scalable reporting and insights. WHAT WE'RE LOOKING FOR - 0–2 years of experience in data analytics, data science, or a related field (internships welcome). - Strong SQL skills & basic Python familiarity. - Experience with BI tools (Omni, Looker, Tableau, etc.) a plus. - Experience working with product analytics tools like PostHog or Google Cloud Analytics a plus. - Deep curiosity and problem-solving mindset, ready to thrive in a hyper-growth Series B setting. - Clear communicator who enjoys working with cross-functional teams. - Excited to work in a fast-paced startup environment and learn quickly. WHAT WE OFFER - Competitive salary and meaningful equity in a high-growth company - Comprehensive medical, dental, and vision coverage - Flexible PTO and paid family leave - Home office & equipment stipend - Hybrid NYC office culture (3 days in-office/week) with direct access to leadership - In-Office Lunch & Dinner Provided PermitFlow provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, s ... (truncated, view full listing at source)
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