Senior Finance Analytics Engineer at Faire in New York, NY

  • Company: Faire
  • Location: New York City, NY | San Francisco, CA
  • Job type: full time
  • Workplace: remote
  • Posted: 2026-09-22

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Job description

About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About this role We're looking for an experienced Senior Finance Analytics Engineer to scale a critically important function responsible for building and maintaining the systems, pipelines, and data models that let us understand financial performance and unlock key business insights at Faire. The ideal candidate will ensure key accounting procedures are automated in ways that are accurate, efficient, easy to understand, and scalable. This role sits in the Finance department and collaborates with team members from a breadth of functional groups across Faire, including Accounting, Finance & Strategy, Engineering, and Data Infrastructure. It has a tremendous impact on Faire employees' ability to use data effectively — both to report numbers externally and to make impactful decisions internally. As a senior member of a growing team, you'll help write the roadmap for how we improve access to business-critical data and unlock automation that amplifies the impact of a variety of functions. What you’ll do Scope, design, build, and maintain complex ETL/ELT pipelines that aggregate and synthesize key business performance metrics and financial reporting, using engineering best practices to keep data models efficient, accurate, and scalable Act as a trusted analytical and technical partner to the Accounting and Finance teams — gathering requirements, providing technical expertise, and enabling data-driven decision-making by ensuring core ledgers accurately reflect business changes Collaborate closely with Engineering and Data Infrastructure to manage and improve data integrations (e.g., Fivetran connectors, S3 pipelines, and other ingestion patterns) and ensure alignment and efficiency across the organization Implement and maintain monitoring, alerting, and testing for data workflows to ensure high data quality and reliability, and champion CI/CD and other engineering best practices within the team's pipelines Lead initiatives to drive data strategy, roadmap planning, and prioritization, ensuring alignment with business objectives, and act as a thought leader who expands the team's influence and impact throughout Finance and the broader organization Drive workflow automation and innovation across Finance, including identifying and implementing Gen-AI–enabled productivity solutions to modernize processes and increase team leverage Qualifications Must have: 5+ years of work experience in Analytics Engineering, Business Intelligence, Data Analytics, or a comparable function Expert in SQL, with a focus on data modeling, large-scale data processing, and tool development for analytics or financial use cases Proven ability to design and maintain production-grade ETL/ELT workflows, including experience with analytics workflow tools (e.g., Airflow, Docker, dbt), data warehousing (e.g., Snowflake, BigQuery, Redshift, S3), and data visualization tools (e.g., Mode, Tableau, Looker) Working proficiency in Python (or a similar language) for pipeline development, automation, and tooling Comfortable working with CI/CD practices and version control (Git) for production data pipelines, including command-line tooling for workflow automation Strong communica

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