Senior Data Engineer, Personalization

Posh•New York, NY

8d•Onsite

About The Position

At Posh, you'll help shape our platform that brings people together through live events. Your work will directly impact how event organizers create experiences and how attendees discover and enjoy them. We're looking for someone who excels in both technical skills and leadership. You'll tackle exciting projects that push our platform forward. Some recent work includes building a system for users to follow each other, creating curated event playlists, and tools for affiliate event promotion. If you enjoy solving real-world problems and working in a fast-paced environment, you'll fit right in. This is an in-person role based in our New York City office in the heart of SoHo. Building live experiences and building with soul are important for our customers, and we believe being and working together as a team is the best way for Posh to feel and achieve this. Events on Posh should be fun, alive, and driven with passion and we want to mirror this in our teams every day!

Requirements

5+ years of experience leading complex technical projects with significant business impact.
Experience integrating LLM or ML outputs into core product features.
Possesses strong specialization in backend or infrastructure systems while maintaining broad knowledge of the full stack.
Proficiency in relevant technologies (IaC, AWS, Java, Python, Typescript), with experience in backend systems.
Experience with scalability, performance optimization, and building tools that support data-driven decision-making.
Strong problem-solving skills and a passion for creating products that connect people in the real world.
Ability to lead initiatives, mentor others, and communicate effectively across technical and non-technical teams.

Nice To Haves

Experience working at consumer, social, or marketplace companies is a plus, as it speaks to our user-centric values at Posh.

Responsibilities

Lead the productionalization of personalization and classification algorithms.
Build with data and analytics in mind, to ensure continued accuracy and relevance of personalization, classification, and ranking algorithms.
Translate experimental outputs (from AWS Sagemaker/Personalize) into production-ready systems, ensuring efficiency and reproducibility.
Demonstrate full stack experience with specialization in backend or infrastructure while contributing to broader projects.
Collaborate on architecture and technical decisions that influence the direction of the platform, ensuring scalability, performance, and user-focused improvements.
Design and maintain model-serving infrastructure, including APIs, batch pipelines, or streaming systems required to deploy ML models reliably.
Build with data and analytics in mind, to ensure continued accuracy and relevance of personalization and classification algorithms.
Focus on performance optimization and system reliability, especially as our user base grows.
Drive experimentation with MVPs, balancing rapid iteration with long-term sustainable growth and developer experience.
Provide mentorship to engineers, fostering a culture of growth and collaboration.