At Neighbor, we’re 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 already flourishing in all 50 states and we’re just getting started!
As a Software Engineer, Data, you will be the core engineer responsible for building, scaling, and optimizing the data infrastructure that transforms raw events into high-fidelity, actionable intelligence. You will pioneer a foundation of engineering excellence, enabling the entire organization to make reliable, data-driven decisions at scale across all 50 states.
You'll join our data & analytics team as its first dedicated data engineer, working alongside data analysts and data scientists. You'll own the pipelines and transformation layer that power analytics at Neighbor: ingesting data from production databases, APIs, and event streams, and serving it through our semantic layer and BI tools. You'll be the engineering backbone of a small, high-leverage data team.
Our stack: dbt and Dagster on Redshift and Athena, with Superset for BI.
At Neighbor, we’re 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 already flourishing in all 50 states and we’re just getting started!
As a Software Engineer, Data, you will be the core engineer responsible for building, scaling, and optimizing the data infrastructure that transforms raw events into high-fidelity, actionable intelligence. You will pioneer a foundation of engineering excellence, enabling the entire organization to make reliable, data-driven decisions at scale across all 50 states.
You'll join our data & analytics team as its first dedicated data engineer, working alongside data analysts and data scientists. You'll own the pipelines and transformation layer that power analytics at Neighbor: ingesting data from production databases, APIs, and event streams, and serving it through our semantic layer and BI tools. You'll be the engineering backbone of a small, high-leverage data team.
Our stack: dbt and Dagster on Redshift and Athena, with Superset for BI.
Primary 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 our 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 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