Senior Analytics Engineering Manager

The Role

The Analytics Engineering team at Nextdoor transforms diverse data sources into solutions for business challenges. As a Senior Analytics Engineering Manager, you will develop and own the vision for Analytics Engineering, delivering curated datasets, dashboards, and internal data products.

Impact You’ll Make

• 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.
• Guide architectural and operational excellence across ETL/ELT pipelines, championing best practices in code review and version control for enhanced reliability.
• 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 AE teams deliver impact (without sacrificing rigor and decision quality).

Bonus Points

• Experience with consumer products, user-generated content, and ad-supported business models.
• Proficiency with version-controlled code (e.g., GitHub) and scripting in Python.
• Experience with agile or kanban workflows.