data
Posted Dec 19, 2025Analytics Engineer
at PermitFlow
New York City, United StatesHybrid
Responsibilities
- - 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.
- - Implement data governance to ensure consistency, quality, and security.
- Define key metrics, track data lineage, and enforce data quality checks. - Work closely with stakeholders to deliver analytics solutions, develop dashboards, and provide training on data tools and best practices. - Manage and optimize PermitFlow’s data stack to support scalable reporting and insights.
Requirements
- 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.
- 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.
- You’ll work closely with engineers, product teams, and stakeholders to ensure data integrity, optimize analytics processes, and support decision-making across the company.
- experience in analytics engineering, data engineering, or data analytics roles. - Strong proficiency in PostgreSQL, SQL, dbt, or similar data warehousing technologies. -
- Experience with ETL pipelines and tools, or other modern data stack tools. - Advanced programming skills in Python or other languages for data transformation and analysis. - Proven
- experience designing data models and building scalable data warehouses for analytics purposes. - A deep understanding of data governance, data quality practices, and developing self-serve analytics solutions. - Strong communication and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders. -
- Experience with business intelligence tools like Looker, Tableau, or Power BI, and familiarity with cloud platforms like Google Cloud.