Role Description As an Analytics Engineer 4 with Nextdoor, Inc. (San Francisco, CA) (May telecommute from any U.S. location) you’ll: - Apply mathematical or statistical theory and methods to design, create, and select the appropriate samples of data that will allow the data science team to conduct probabilistic experiments and statistical analyses. - Design software systems and processes to gather data in the most efficient way and determine key data points needed in order to interpret experiment results and ensure results are properly tracked. - Interpret data and report conclusions drawn from their analyses. - Work with cross-functional teams, including product, design, engineering, marketing, operations, and sales, to determine which data analyses will lead to the most actionable insights. - Build data pipelines to create and transform data for analysis of different product features. - Clean and summarize data to make it accessible for reporting and for data science. - Combine data from multiple sources to make and distribute client reports in order to see how particular ad products are performing. - Analyze expected vs actual delivery of ad products in order to find and improve gaps in our delivery pipeline. Qualifications - Master’s degree or foreign equivalent in Mathematics, Statistics, Business Analytics, or closely related quantitative field. - Three (3) years of experience in the role or in a related position. - Full term of experience must include the following: - Utilizing Data Analysis tools, such as Databricks or Snowflake, to support and improve business. - Utilizing Python and Structured Query Language (SQL) programming languages to conduct large scale data analyses. - Utilizing data processing languages, including Airflow or Alteryx, to build big data pipelines to extract and transform data. - Utilizing Tableau or Looker to generate reports and build dashboards and analyze data and create data insights. - Utilizing advanced MS Excel Functions, including VBA coding, Pivot Tables, and Power Point, to present project reports and recommendations to leadership teams. - Utilizing data analysis skills to collect large data sets to uncover and visualize hidden insights in core data. Benefits - The starting salary for this role is expected to be: $175,000 - $180,000/year. - We also expect to award a meaningful equity grant for this role. With equal quarterly vesting, your first vest date would be within the first 3 months of your start date. - Overall, total compensation will vary depending on your relevant skills, experience, and qualifications. - Nextdoor employees can choose between a variety of great health plans. We cover 100% of your personal monthly premium for health, dental, and vision – and provide a OneMedical membership for concierge care.

• As a Staff Analytics Engineer, you will own BeReal’s product analytics layer end-to-end. • Act as the most senior voice on analytics, reporting directly to the VP Engineering. • Partner closely with Product Managers, Engineers, and Data stakeholders to build a scalable, reliable, and self-service analytics foundation that empowers better product decisions. • Define and execute BeReal’s product analytics roadmap, aligning modeling, observability, and tooling with product priorities. • Partner closely with Product Managers to translate product loops, retention mechanics, and experimentation needs into scalable data models. • Build and deploy AI-powered internal analytics tools that enable stakeholders to query data in natural language. • Own the integration between BigQuery, Amplitude, and our experimentation framework to ensure a single source of truth for metrics. • Design and maintain a self-service metrics layer that enables PMs to independently analyze funnels and experiments. • Write production-grade dbt models and optimize SQL transformations for reliability, performance, and scalability. • Lead technical reviews and establish best practices for analytics engineering. • Collaborate with Backend and Mobile teams to ensure analytics instrumentation is robust and analytics-ready from day one. • Monitor data quality and observability to guarantee trust in product metrics and reporting.

• Plan and execute on technology projects that scale with Faire’s growth; lead architecture development with a focus on data integrity, security, performance, scale, reliability, monitoring/alerting. • Engage with team planning and prioritization, balancing urgent and near-term needs with long-term goals. • Provide technical guidance and mentorship on the most difficult open-ended problems we face. Including cost-efficient compute and storage, ETL and ELT pipelines, data ingest and warehousing, monitoring, alerting, and cost tracking for workloads, design practices for foundational assets, data security, privacy, and governance.

• Build and maintain scalable, secure ETL/ELT pipelines, ingestion systems, and transformation workflows across distributed cloud data warehouses. • Optimise for query performance, cost, and scalability as data volumes grow. • Establish standard data schemas, dimensional modeling structures, and automated validation tests to enforce data accuracy, consistency, and downstream reliability. • Manage and optimize backend data layers feeding business intelligence systems, reporting engines, and analytical discovery platforms. • Conduct query performance tuning, data partitioning analysis, and infrastructure scaling to control computational overhead and latency within cloud data lakes. • Partner with business units, IT leadership, and software engineers to translate business requirements into sustainable data engineering architectures.