Staff Data Engineer (Data Platform)

OUR STORY

Quince was started to challenge the existing idea that nice things should cost a lot. Our mission was simple: create an item of equal or greater quality than the leading luxury brands and sell them at a much lower price.

OUR VALUES

Customer First. Customer satisfaction is our highest priority.

High Quality. True quality is a combination of premium materials and high production standards that everyone can feel good about.

Essential design. We don't chase trends, and we don't sell everything. We're expert curators that find the very best and bring it to you at the lowest prices.

Always a better deal. Through innovation and real price transparency we want to offer the best deal to both our customers and our factory partners.

Environmentally and Socially conscious. We're committed to sustainable materials and sustainable production methods. That means a cleaner environment and fair wages for factory workers.

OUR TEAM AND SUCCESS

Quince is a retail and technology company co-founded by a team that has extensive experience in retail, technology and building early stage companies. You'll work with a team of world-class talent from Stanford GSB, Google, D.E. Shaw, Stitch Fix, Urban Outfitters, Wayfair, McKinsey, Nike etc.

About the role

We're looking for a Staff Data Engineer to help design and build our next-generation data platform from the ground up. This is a high-impact, hands-on role where you'll define core architectural decisions, set engineering standards, and partner closely with analytics, product, and engineering teams to unlock data at scale.

If you enjoy building platforms (not just using them), making long-term technical bets, and mentoring strong engineers, this role is for you.

Responsibilities

• Architect and build the foundational data platform that powers analytics, experimentation, and data products
• Establish best practices for data modeling, orchestration, testing, and observability
• Build and optimize data infrastructure on AWS (storage, compute, networking, security)
• Partner with stakeholders across Product, Analytics and Engineering to translate business needs into robust data solutions
• Drive technical decisions around performance, cost optimization, and data quality
• Mentor and guide other data engineers, raising the bar for technical excellence across the team
• Own critical systems end-to-end and participate in long-term platform roadmap planning
• Ensuring operational efficiency and actively participating in organizational initiatives with the objective of ensuring the highest customer value.

Must Have:

• 6+ years of experience in data engineering or platform engineering roles
• Strong hands-on experience with Spark, Python, and SQL in production environments
• Experience designing and operating large-scale data systems on cloud infrastructure (AWS preferred)
• Deep understanding of data modeling, distributed systems, and performance tuning
• Proven ability to lead technical initiatives and influence architecture across teams
• Comfortable working in ambiguous, early-stage environments where you help define the right way

Good To Have:

• Experience with Trino (or similar distributed SQL query engines)
• Experience using dbt for data transformations and modeling
• Familiarity with modern data stack concepts (lakehouse architectures, columnar storage, open table formats)
• Experience building internal data platforms or shared infrastructure
• Experience with Kubernetes, particularly Amazon EKS, for deploying and operating data workloads
• Proficiency in Apache Spark & Apache Kafka.