Growth Product Manager, Marketing Technology

About Poshmark

Poshmark is the leading fashion marketplace where style comes alive through discovery, self-expression, and human connection. Powered by a vibrant community of 165 million members, Poshmark brings real people and taste to shopping through a social experience shaped by shared discovery. Buying and selling fashion feels simple, joyful, and personal, while every item tells its own story. Poshmark empowers sellers to grow meaningful businesses, keeps fashion in circulation longer, and gives shoppers access to unique and trusted finds, from everyday pieces to one-of-a-kind vintage and luxury.

Role Overview

This role sits at the intersection of product, data, and customer communication. You will own Poshmark's marketing technology stack, including our customer engagement platform (CEP), customer data platform (CDP), email, push notifications, promotional systems, and CRM strategy for our merchandising and seller teams. The work here is both strategic and deeply technical. On any given week you might be evaluating CDP architecture decisions, running send time optimization experiments, defining segmentation logic for a seller re-engagement campaign, or partnering with engineering to improve our transactional email template system. The common thread is that you own the infrastructure and the outcomes, not just the roadmap.

What You Will Own

• Customer Engagement Platform (CEP) and Channel Orchestration:
• Define the orchestration logic across channels: which message, to which user, through which channel, at what moment
• Lead personalization initiatives including our ML-powered delivery timing program, working closely with data science on model inputs, evaluation, and rollout
• Set the standard for email and push quality and deliverability health, partnering with engineering and marketing ops to monitor performance and resolve issues quickly
• Own the roadmap for how we expand CDP usage over time, including new activation use cases across email, push, and paid channels
• Customer Data Platform (CDP) and Data Infrastructure:
• Define the data model for how customer attributes, behavioral signals, and lifecycle events flow from our data warehouse into our engagement systems
• Own the implementation strategy and long-term product roadmap, connecting our Redshift data warehouse to downstream engagement tools to improve how we build audiences and activate data at scale
• Partner with data engineering to ensure audience definitions are accurate, refreshable, and auditable
• Email, Push, and Promotional Messaging:
• Set the standard for email and push quality and deliverability health, partnering with engineering and marketing ops to monitor performance and resolve issues quickly
• Own the product layer for promotional campaigns including discount mechanics, offer construction, audience targeting, and measurement
• Own the product strategy across all three, setting standards for message quality, channel coordination, experimentation, and performance
• Define how promotional events interact with our broader lifecycle programs so messaging is coordinated, not redundant
• CRM for Merchandising:
• Build the product workflows that allow the merchandising team to trigger targeted, interest-based outreach at scale without requiring engineering every time, shifting the communication model from program-driven batch sends toward user-centric engagement
• Partner with the merchandising team to understand their shopper and seller communication needs and translate those into durable platform capabilities

What We Are Looking For

• Martech Platform Expertise:
• 4+ years in a product management or growth engineering role with direct ownership of a martech stack
• Hands-on experience with a customer engagement platform (MoEngage, Braze, Iterable, Salesforce Marketing Cloud, or similar) at a product or implementation level, not just a user level
• Working knowledge of how CDPs function: data ingestion, identity resolution, audience construction, and downstream activation
• Comfortable with the data layer: SQL fluency, understanding of event schemas, and ability to work directly with data engineers on pipeline and model design
• Comfortable reading API documentation, reviewing data schemas, and holding a technical conversation with engineers and data scientists as a peer
• Track record of running structured experiments across owned channels with proper methodology: experiment sizing, holdout groups, attribution, and incremental lift measurement
• Understanding of the difference between correlation and causation in lifecycle data, and how to design tests that actually answer the question you are asking
• Experience working with incrementality measurement frameworks is a plus
• Execution:
• Willing and able to use AI-assisted development tools (Codex, Claude Code, or equivalents) to build prototypes, draft specs, and accelerate your own output
• Own channel performance, not just feature launches. If email open rates drop or push opt-outs spike, you are the first to diagnose and address the problem
• Build strong working relationships with engineering, data science, and marketing ops proactively, not reactively when something breaks
• Communicate decisions and tradeoffs to senior leadership with a clear point of view, not a list of options

Nice to Have

• Experience at a consumer marketplace with active seller and buyer communication programs (Etsy, eBay, Whatnot, Depop, or similar)
• Background in email deliverability: domain reputation, list hygiene, ISP relationships, and inbox placement
• Prior work on AI-driven personalization systems, recommendation-based messaging, or predictive audience models
• Experience integrating a composable CDP (Hightouch, Segment, or similar) with a downstream engagement platform