Data Platform Engineer

Owner.com

2d•$190,000 - $220,000•Remote

About The Position

We are looking for a mission-driven Data Platform Engineer to build Owner's data platform - the foundational systems that power analytics, AI, and decision-making across the company. The Data Platform team owns everything data flows into and out of: ingestion, transformation, storage, orchestration, and the reverse ETL, semantic layers that put data back in the hands of the teams and products that need it, and infrastructure for our internal BI system. Today that system works, but part of it was built outside of SOT (in Hex) and needs to be migrated into DBT. You'll replace it with reproducible, production-grade infrastructure - and then make it self-service for the analysts, engineers, and AI systems that depend on it. This is an exciting role to build out the foundations of our data platform. The team is four engineers and growing, there is very little legacy to work around, and the decisions you make in your first year will define how Owner uses data for years. Depending on your interests, there is room to focus on core pipeline and platform infrastructure, or on the semantic layer that sits between LLMs and our data and defines how AI queries it. This role is 100% remote and can be based anywhere in the United States or Canada. For San Francisco-based candidates - we also have a new HQ in the Presidio for optional in-person collaboration.

Requirements

5+ years of data engineering or analytics engineering experience
Strong SQL and Python fluency
Hands-on production experience with Snowflake
Deep ETL/ELT fundamentals, including dbt and a modern orchestrator such as Dagster or Airflow
Proven track record of impact-driven problem-solving in fast-paced environments, with a strong focus on high-quality, reliable, and performant systems
Excellent technical communication skills, with experience collaborating across both technical and non-technical stakeholders
Comfort building from zero - strong opinions, real energy for the work, and the ability to create structure where none exists
A sense of ownership, curiosity, and commitment to continuous learning

Nice To Haves

Experience building a semantic layer, or data infrastructure for AI/ML and LLM retrieval (RAG, feature stores, dataset compliance)
Experience with reverse ETL or personalization platforms
Databricks experience (we run Snowflake today)
Experience with data governance, access control, and cost optimization for large-scale data platforms
Experience mentoring engineers and fostering a culture of learning and technical excellence
Genuine interest in the product and our customers - helping local businesses succeed, not infrastructure for its own sake

Responsibilities

Design and build the data systems that power analytics, AI, and business intelligence across Owner
Replace one-off custom scripts with reproducible, production-grade pipelines
Own and evolve our core platforms - Snowflake, dbt, Dagster, and our ingestion and reverse ETL layers
Improve data reliability, consistency, and compliance so every stakeholder can trust the numbers
Move the team to self-service tooling for analysts and partners
Identify and drive cost and performance optimizations across compute, storage, and processing
Drive technical decisions and best practices for ingestion, transformation, orchestration, and storage
Provide thoughtful code reviews and technical guidance to peers, and help us build a great team