Software Engineer, Data

About Neighbor

Neighbor is building the largest hyperlocal marketplace the world has ever seen. We’ve raised over $75 million from top-tier investors such as Andreessen Horowitz and the CEOs of DoorDash, StockX, and Uber. Our marketplace is flourishing in all 50 states, connecting storage facilities, neighborhood garages, driveways, and RV spots in one simple search. Join us to disrupt the $500 billion storage and parking industry as part of a fast-growing, VC-backed tech startup.

About the Role

As the first dedicated Data Engineer on our data & analytics team, you will build, scale, and optimize the data infrastructure that transforms raw events into high-fidelity, actionable intelligence. You’ll pioneer engineering excellence, enabling the entire organization to make reliable, data-driven decisions at scale. You’ll own the pipelines and transformation layer powering analytics at Neighbor, working alongside data analysts and scientists to ingest data from production databases, APIs, and event streams, and serve it through our semantic layer and BI tools.

Our stack: dbt and Dagster on Redshift and Athena, with Superset for BI.

Responsibilities

• Design and build robust pipelines to ingest data from diverse sources (APIs, logs, relational DBs).
• Ensure the reliable and timely execution of all critical data pipelines (ETLs/ELTs) to maintain data integrity and freshness.
• Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols.
• Develop and refine a robust semantic layer to facilitate self-service analytics, enabling stakeholders to derive insights without exposure to underlying architectural complexities.
• Monitor and optimize cloud compute utilization and data model performance to ensure high availability and low-latency reporting during periods of rapid data scaling.
• Serve as a strategic technical partner to leadership across Product, Engineering, Marketing, and Finance to align data infrastructure with organizational objectives.
• Become a subject matter expert on the product ecosystem, user behavior, and marketing life cycles to better translate raw data into business value.
• Go deep on analysis yourself when the question demands it; you're comfortable in both the pipeline and the insight.
• Mentor data analysts and data scientists on engineering best practices (code review, testing, version control, pipeline design), raising the technical bar across the team.

Qualifications

• 5+ years as a software engineer, including 3+ years with an emphasis in data engineering or analytics engineering.
• Bachelor's degree in quantitative and/or technical fields (Math, Physics, Statistics, Economics, Computer Science, Engineering, etc.) or equivalent practical experience.
• Expert-level mastery of SQL, with the ability to write, tune, and optimize complex queries for high-volume environments.
• Hands-on experience designing and maintaining data lakes or cloud-based data warehouses.
• Deep understanding of data integration patterns, including data ingestion, transformation, and automated cleansing (ETL/ELT).
• Advanced ability to translate complex datasets into actionable narratives using modern business intelligence and reporting tools.
• A proven track record of using quantitative analysis to solve ambiguous problems and drive strategic decision-making in a fast-paced environment.
• Exceptional ability to collaborate with non-technical stakeholders, translating business requirements into technical specs and vice versa.

Benefits

• Generous stock options.
• Medical, dental, and vision insurance.
• Generous PTO.
• 11 paid company holidays.
• 401(k) plan.
• Infant care leave.
• On-site gym/showers open 24/7.