Senior Software Engineer I, Data Enablement

Etsy•New York, NY

5d•$164,000 - $193,000•Hybrid

About The Position

Etsy's Data & ML Enablement organizations build the platforms, systems, and infrastructure that power internal teams to transform raw data into reliable insights and production-grade ML systems. The Data Enablement org is standing up a team of engineers who will sit at the intersection of these platforms and the product teams that depend on them. As a member of this team, you will embed with partner teams working on complex, high‑impact projects and help them successfully onboard to the Data and ML Enablement stack. You’ll design and implement integrations, data flows, and ML feature pipelines that turn platform capabilities into shipped outcomes, so teams can accelerate experimentation into real impact. You’ll focus on applying existing Data and ML Enablement offerings (events, canonical datasets, training and inference infrastructure, embeddings, etc.) to real product problems. You’ll also play a critical role in closing the loop with our platform teams by providing concrete, actionable feedback that improves developer experience and unlocks new use cases. We work in Scala, Python, Java, and SQL, and we partner closely with systems built on Spark, Kafka, Airflow, Looker, BigQuery, and other Google Cloud Platform (GCP) services. Experience with any of these is helpful but not required; above all, we value curiosity, enthusiasm, responsibility, and generosity of spirit. We’re looking for a flexible engineer who cares about the data and ML capabilities they’re integrating, and about the internal customers who will rely on those solutions every day. You’re excited to pivot to the right tool for the job, learn new systems quickly, and help other teams succeed on top of our platforms rather than reinventing them. This is a full-time position reporting to the Senior Engineering Manager, Core Data. In addition to salary, you will also be eligible for an equity package, an annual performance bonus, and our competitive benefits that support you and your family as part of your total rewards package at Etsy. For this role, we are considering candidates based in the United States. Candidates living within commutable distance of Etsy’s Brooklyn Office Hub or in the San Francisco Bay Area may be the first to be considered. For candidates within commutable distance, Etsy requires in-office attendance once or twice per week depending on your proximity to the office. Etsy offers different work modes to meet the variety of needs and preferences of our team. Learn more details about our work modes and workplace safety policies here. We embed directly with teams working on complex, high‑impact initiatives such as new personalization models, buyer and seller experiences, or metrics and experimentation frameworks and ensure they can successfully adopt our data and ML platforms end‑to‑end. We take ambiguous, cross‑functional problems and help teams turn them into concrete architectures, integration plans, and production‑ready implementations on top of existing platform capabilities. We focus on accelerating adoption, reducing integration friction, and improving developer experience for our internal customers. We act as a feedback conduit from implementation back into platform teams, surfacing usability gaps, missing primitives, and opportunities for simplification.

Requirements

A consistent track record of working with batch and streaming distributed systems (Spark, Kafka, Airflow) and cloud platforms (Google Cloud, AWS, etc.).
Experience with machine learning systems and infrastructure, with interest in learning how large-scale ML platforms are built and operated.
Strong software engineering skills, with the ability to write production-ready code in Java, Scala, Python, and/or other equivalent languages.
A strong customer mindset: you enjoy collaborating directly with partner teams, understanding their workflows and constraints, and helping them succeed on top of our platforms.
You are generous with your time and experience, and can mentor and learn from other engineers.
You have curiosity about understanding the e-commerce industry and the vast amount of data generated by the different functions of the company.

Nice To Haves

Experience with Scala, Python, Java, and SQL.
Experience with Spark, Kafka, Airflow, Looker, BigQuery, and other Google Cloud Platform (GCP) services.

Responsibilities

Partner with product engineering, ML and analytics teams to scope new projects that depend on the Data and ML Enablement stack, clarifying requirements and mapping them onto existing capabilities.
Help teams migrate ad‑hoc or legacy pipelines onto canonical data sources and standardized paved paths, reducing duplication and long‑term maintenance burden across the company.
Debug and unblock tricky integration issues spanning multiple systems (e.g., events → canonical datasets → feature stores → training data → inference services), collaborating closely with platform owners where needed.
Document patterns, examples, and “recipes” for successful integrations so future teams can move faster with less direct support.
Provide structured, actionable feedback to Data and ML Enablement teams on gaps in APIs, tooling, documentation, and paved paths, based on what you see in the field.