Staff Data Engineer

About Breezy

Founded in early 2024 by top-producing agent James Harris, Afterpay Co-Founder and seasoned technology entrepreneur Nick Molnar, and leading venture capitalists, Breezy is the AI-powered operating system built exclusively for residential real estate professionals. Despite being the backbone of every transaction, agents remain chronically underserved by technology—many still rely on notes and spreadsheets to manage multimillion-dollar businesses.

Breezy handles every aspect of an agent's day — pulling branded comps on the go, taking meeting notes and sharing them with clients, updating pipelines automatically, and surfacing build-potential insights no one else has

In three weeks, Breezy reached 7,500 installs with a 97% sign-up and trial-activation rate, signaling strong user intent and real product market fit

Proprietary data platform

Our main claim to fame is our unique data platform that pulls zoning information and municipal guidelines into an “underbuilt” report agents can generate in seconds. An agent can type in a home address and immediately uncover how much build potential a lot has , answering questions like “can I add a basement, a second floor, an ADU”, etc.

This is the kind of insight that used to require hiring a surveyor, waiting three weeks, and spending thousands of dollars. We're delivering that in seconds.

As we keep building our engine, processing millions of MLS and property records, as well as other sources of residential data, we are looking for two key stakeholders

Staff Data Engineer
About the Role

Breezy is building a data platform for residential real estate. We process millions of MLS and property records. We need a Staff Data Engineer to lead this platform's growth.

Problems You'll Own

1. Scaling Our Data Pipeline. We currently manage 14 AWS Glue jobs with bash scripts and EventBridge. You'll create a scalable platform for teams to build on.
2. Managing Multi-Destination Data Architecture. Property data must go to Postgres, Apache Iceberg on S3, ClickHouse, and OpenSearch. Each has different needs. You will ensure consistency and efficiency
3. Improving Data Quality: We have basic anomaly checks, but we need a better approach. You'll focus on data quality, including lineage, regression testing, and pipeline health monitoring
4. Supporting New Data Initiatives. As our product evolves, we will integrate new data sources. You'll make this happen

What You'll Do

• Design and build reliable data pipelines for property data across various storage engines
• Manage data from raw delivery to production-ready layers
• Develop orchestration and observability tools to replace ad-hoc scripts
• Collaborate with product engineers on data contracts and APIs
• Decide on tooling, such as Airflow or EventBridge
• Set technical standards for data engineering at Breezy

You'll Work With

• Python and SQL daily, using Glue jobs, Postgres/PostGIS RPCs, and Iceberg/Athena queries.
• AWS services like Glue, S3, Athena, EventBridge, and OpenSearch.
• Many Storage Engines, including Postgres, Apache Iceberg, ClickHouse, and OpenSearch.
• Data Formats like Parquet, Iceberg table format, and bulk CSV/TSV.
• Infrastructure-as-Code using OpenTofu/Terraform.
• TypeScript and NestJS are used from time to time for the ClickHouse analytics API and ingestion service.

What We're Looking For

• 8+ years in data engineering, with 2 years at a staff or principal level.
• Experience building a data platform from scratch.
• Strong Python and SQL skills.
• Knowledge of AWS data services and various storage engines.
• Ability to make independent infrastructure decisions and explain them clearly.
• Comfort in a fast-paced startup.

Nice to Haves

• Experience with Apache Iceberg, ClickHouse, or columnar OLAP systems.
• Knowledge of real estate, MLS, or proptech.
• Experience with PostGIS or geospatial data at scale.
• Background in building data foundations for ML/AI workloads.
• Familiarity with OpenTofu/Terrafor