Engineering Manager (Data Engineering)

Quince · Bengaluru, Karnataka, India

  • Senior
  • Full-time
  • Posted 2026-09-22
  • Confirmed live on 25 September 2026

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Job description

ABOUT QUINCE

Quince is a destination for builders, creators, innovators, and operators who want to come together and challenge the status quo. Our mission is simple: make really high quality essentials for really low prices, fairly and sustainably. We deliver on that mission through a unique manufacturer-to-consumer (M2C) model eliminating the layers of traditional retail that add cost and result in consumers paying more than they need to. We find, build relationships with, and work directly with the manufacturing partners behind some of the world’s finest products. From there, our teams design smart, efficient operational processes and build and deploy proprietary technology, AI, and analytics to help us scale fast.

What began with a small assortment of elevated basics has quickly grown into a cross-category brand spanning apparel, accessories, home goods, and more. Today, tens of millions of people across a growing number of countries come – and return – to Quince because they trust us to deliver.

OUR CULTURE

Quince is a culture built for builders by builders. Our way of working starts with a blank sheet of paper. We question conventional thinking, use technology and data to uncover new opportunities, and move quickly to turn ideas into reality. We aren’t interested in replicating how others do retail. We’re building a better way – at a speed and scale unlike anything that’s been done before.

• We dream big and chase the hard problems others shy away from. Rejecting long-held assumptions is part of our company's DNA. Where conventional wisdom says you have to choose – soft or durable, speed or rigor, quality or price – we ask why that trade-off has to exist in the first place.

• Our pace is fast and the bar is high because our customers expect a lot from us and we refuse to let them down. We believe the best results come from challenging ourselves, learning from one another, and building on each other's strengths.

• Here, responsibility is not determined by role, tenure, or seniority. Every team member - no matter their level - has the opportunity to drive our business and shape our trajectory.

If you’re someone who likes to imagine new possibilities and build better systems rather than plug-in to outdated ones, Quince is the place for you.

THE ROLE

Engineering Manager (Data Engineering)

We’re looking for an Engineering Manager to lead the Data Products team — the engineers who own the ETL pipelines and curated datasets behind Quince’s core business domains.

This is a delivery- and ownership-heavy leadership role. You’ll own the datasets that the business runs on: how they’re modeled, how reliably they land, how well they’re documented, and how much they cost to produce. You’ll lead a team of data engineers embedded against business domains, set the modeling and quality bar across them, and act as the primary engineering partner to Analytics, Marketing, and Product.

If you like turning messy upstream systems into trustworthy, well-modeled data products — and building the team and standards that keep them trustworthy — this role is for you.

Responsibilities

Team Leadership & Development

• Lead, grow, and develop a team of data engineers owning domain-aligned data products, including hiring, onboarding, coaching, performance management, and career growth.

• Build strong working relationships with engineers across the team, understand strengths and development areas, and establish clear growth plans.

• Ensure operational efficiency and actively participate in organizational initiatives with the objective of ensuring the highest customer value.

Data Products & Dataset Ownership

• Own the end-to-end lifecycle of domain datasets: ingestion, transformation, modeling, publication, documentation, and deprecation.

• Own delivery of the domain ETL roadmap, including prioritization, sequencing, commitments, and predictable execution across multiple business stakeholders.

• Own freshness, accuracy, and availability SLAs for critical datasets, along with the on-call and incident response process that protects them.

• Establish clear ownership and data contracts between the Data Products team, upstream service teams, and downstream consumers.

Data Modeling & Engineering Standards

• Set and enforce standards for data modeling, including dimensional and semantic layers, transformation patterns, testing, and code review across domains.

• Drive data quality and observability practices through checks, alerting, lineage, and root-cause discipline so issues are caught before consumers find them.

• Identify opportunities to improve reliability, freshness, modeling quality, delivery predictability, and cost.

Data Platform & Technical Operations

• Partner with the Data Platform team to translate domain needs into platform capabilities and drive adoption of self-serve tooling within the team.

• Manage the compute and storage cost of domain pipelines and drive measurable efficiency improvements.

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