Data Engineer
Primary Responsibilities
- Design, implement, and maintain scalable data transformation layers and code-first orchestration frameworks to ensure the delivery of high-fidelity, reusable data models
- 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
- Serve as a versatile technical resource capable of stepping into the Data Analyst capacity when necessary—performing deep-dive quantitative analysis and building sophisticated visualizations to support executive decision-making
- Mentor the data analytics team on advanced technical methodologies to foster a culture of engineering excellence and data autonomy
Qualifications
- 3+ years of experience in data engineering or analytics engineering
- Bachelor's degree in quantitative and/or technical fields (Math, Physics, Statistics, Economics, Computer Science, Engineering, etc.) OR 5+ years work experience as a Data Engineer
- Expert-level mastery of SQL, with the ability to write, tune, and optimize complex queries for high-volume environments
- Strong command of at least one major programming language used for data processing
- 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)
- Experience applying scientific, mathematical, or statistical techniques to analyze data and build predictive models
- 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
About the Role
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!
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
Company Information
Neighbor is the largest and most comprehensive marketplace for self storage and parking, with listings in almost every U.S. city. From storage facilities to neighborhood garages, driveways, and RV spots, Neighbor brings every option together in one simple search.
Contact Information
If accommodations due to a disability or medical condition are needed, connect with us via email at hr@neighbor.com. Check out our careers page to get to know us better as you think about your next step at Neighbor! We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.