Senior Analytics Engineering Manager

Nextdoor
San Francisco, CA$181k – $277kPosted 18 April 2026

Job Description

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 340,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors The Analytics Engineering team at Nextdoor transforms diverse data sources into solutions for business challenges. As a lean yet impactful team, we cover the entirety of the Nextdoor business and excel in cross-functional collaboration to empower company-wide data-driven decision-making. By amplifying the voices of our platform's users, we play a pivotal role in building stronger, healthier communities. We’re at an exciting transition, evolving from a traditional Business Intelligence focus to a broader mandate that includes strengthening data foundations and developing data products, such as analytics self-serve, for all Nextdoor data consumers. At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make As a Senior Analytics Engineering Manager , you will Develop and own the vision for Analytics Engineering, delivering curated datasets, dashboards, and internal data products. Define outcomes and communicate prioritization, progress, and impact to leadership Establish and enforce standards for metrics, data governance, documentation, and SLAs, overseeing data quality with proactive issue resolution through alerting and root-cause analysis Build, coach, and elevate a high-performing analytics engineering team, setting clear goals and fostering a culture of inclusion, learning, and operational excellence Collaborate closely with data science, finance, marketing, sales, product, and engineering to prioritize the analytics engineering roadmap and drive data-driven decision-making Scale data self-service and literacy by expanding documentation, training, and enablement in key tools and dashboards, empowering stakeholders to explore data independently Guide architectural and operational excellence across ETL/ELT pipelines, championing best practices in code review and version control for enhanced reliability Cultivate a proactive data product builder culture within the team, shifting from a service-oriented approach to identifying needs, recognizing patterns, and implementing solutions in phases Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises Build in-person relationships with team members and contribute to Nextdoor’s company culture What You’ll Bring To The Team 10+ years in analytics engineering, data engineering, or analytics, with strong hands‑on SQL, Python, and data modeling expertise 3+ years of people leadership experience, including hiring, coaching, and performance management in analytics/data teams Proven ability to define semantic layers and build scalable dashboards; experience with Looker (preferred) or other BI/visualization tools, including in tool selection, setup and governance Experience building and operating ETL/ELT pipelines with robust validation and monitoring; high bar for data quality Excellent communication; proven success partnering with cross‑functional stakeholders (Finance, Product, Engineering, etc.) to define KPIs and deliver measurable outcomes Track record of driving projects end‑to‑end and demonstrating clear outcomes and impact Appetite for applying AI and emerging tools to increase productivity and reimagine how ... (truncated, view full listing at source)
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