Staff Data Engineer (Data Platform)

Bengaluru, Karnataka, India ABOUT QUINCE Founded in 2018, Quince was built to challenge the idea that nice things have to cost a lot. Our mission is simple: to make really high quality essentials for really low prices, produced fairly and sustainably. We believe everyone deserves exceptional craftsmanship and timeless design without the traditional markups. Quince is a direct-to-consumer (DTC) model that cuts out middlemen and leverages just-in-time manufacturing to minimize waste and maximize value. Quince is a tech company disrupting the retail industry by putting AI, analytics and automation at the center of everything we do. Our unwavering commitment to excellence and company values guide our teams and actions:

Customer First: We prioritize customer satisfaction in every decision.
High Quality: True quality means premium materials and rigorous production standards you can feel good about.
Essential Design: We focus on timeless, functional essentials instead of chasing trends.
Always a Better Deal: Innovation and transparency ensure value for both customers and partners.
Social & Environmental Responsibility: We commit to sustainable materials, ethical production, and fair wages.

Quince partners with world-class manufacturers across the globe and serves millions of customers. With strong investor backing and a focus on sustainable growth, we are a company that is rapidly scaling while maintaining a commitment to quality, simplicity, and radical price transparency. OUR TEAM AND SUCCESS At Quince, you will be part of a high-performing team that is redefining what quality, value, and sustainability mean in modern retail. We are a destination for builders, innovators, and operators to come together and challenge the status quo. Our collective ambition is bold. We are creating an entirely new category and customer experience – one that democratizes luxury and provides high quality products at radically low prices. That mission demands a world-class team committed to excellence. If you are motivated by impact, growth, and purpose, you will find a strong sense of belonging at Quince. 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:

7+ 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,...