分析工程经理
Manager, Analytics Engineering
关于Extend:
Extend正在通过提供由人工智能驱动的解决方案,重新定义零售商及其客户的售后体验,从而提升客户满意度并推动收入增长。我们的全面平台提供自动化客户服务处理、无缝的退换货管理、端到端的自动化履行,以及产品和运输保护,同时结合Extend一流的欺诈检测功能。通过将前沿技术与卓越的客户服务相结合,Extend使企业能够建立消费者的信任和忠诚度,同时降低成本并增加利润。
如今,Extend与跨行业的1000多家领先商户合作伙伴合作,包括时尚/服装、化妆品、家具、珠宝、消费电子产品、汽车零件、体育和健身等。Extend得到了业内一些最著名的科技投资者的支持,总部位于旧金山市中心。
关于该职位:
Extend为数百家商户提供产品保护、运输保护和保修计划。这些计划生成的数据驱动定价和精算建模、风险和损失分析、欺诈检测、产品和商户分析,以及财务和收入报告。
Analytics Engineering团队负责所有这些背后的平台:公司所报告的Snowflake仓库和dbt代码库,以及为其提供数据的采集流程,以及保持其运行的管道和监控。Analytics、精算、风险、欺诈、产品、运营、财务、会计和收入团队都基于该团队所产出的内容。
我们正在寻找一位Analytics Engineering经理来领导该团队。你将向我们的高级工程经理(数据工程)汇报。该职位需要亲力亲为,带领一个远程的分析和数据工程师团队。
你将负责:
- 管理和发展团队。包括招聘、入职、职业发展和绩效评估。
- 设定技术标准并负责dbt代码库作为共享平台。审查拉取请求,做出架构决策,并为你的团队以及所有向该仓库提交模型的团队设定测试、文档和CI的标准。合作团队负责其模型中的业务逻辑;你负责他们提交的平台和标准。保持变更控制的严谨性和速度。
- 负责仓库和管道。包括Snowflake、dbt、源数据采集和新鲜度、外部表,以及用于填充它们的AWS Glue/CDK作业。
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About Extend:
Extend is revolutionizing the post-purchase experience for retailers and their customers by providing merchants with AI-driven solutions that enhance customer satisfaction and drive revenue growth. Our comprehensive platform offers automated customer service handling, seamless returns/exchange management, end-to-end automated fulfillment, and product protection and shipping protection alongside Extend's best-in-class fraud detection. By integrating leading-edge technology with exceptional customer service, Extend empowers businesses to build trust and loyalty among consumers while reducing costs and increasing profits.
Today, Extend works with more than 1,000 leading merchant partners across industries, including fashion/apparel, cosmetics, furniture, jewelry, consumer electronics, auto parts, sports and fitness, and much more. Extend is backed by some of the most prominent technology investors in the industry, and our headquarters is in downtown San Francisco.
About the Role:
Extend powers product protection, shipping protection, and warranty programs for hundreds of merchants. The data those programs generate drives pricing and actuarial modeling, risk and loss analysis, fraud detection, product and merchant analytics, and financial and revenue reporting.
The Analytics Engineering team owns the platform behind all of it: the Snowflake warehouse and dbt repository the company reports from, the ingestion that feeds them, and the pipelines and monitoring that keep them running. Analytics, Actuarial, Risk, Fraud, Product, Operations, Finance, Accounting, and Revenue all build on what this team produces.
We’re looking for a Manager, Analytics Engineering to lead that team. You’ll report to our Senior Engineering Manager, Data Engineering. The role is hands-on, leading a remote team of analytics and data engineers.
What You’ll Do:
- Manage and grow the team. Hiring, onboarding, career development, and performance.
- Set the technical bar and own the dbt repository as a shared platform. Review pull requests, make the architecture calls, and set the standard for tests, documentation, and CI for your team and for every team that ships models into the repo. Partner teams own the business logic in their models; you own the platform and standards they ship into. Keep change control rigorous and fast.
- Own the warehouse and pipelines. Snowflake, dbt, source ingestion and freshness, external tables, and the AWS Glue/CDK jobs that feed them.
- Model the core business domains. Orders, contracts, claims, and service orders, defined once so actuarial, risk, fraud, product, and finance all get the same answer. Evolve these models as upstream product systems change, and consolidate warehouse modeling onto the shared platform.
- Evolve the platform. Lead platform migrations, including moving dbt execution to Snowflake-native tooling, and retire legacy components on a planned timeline.
- Partner across the business. Build trusted relationships with internal stakeholders by translating their questions into models, aligning them on shared definitions, and shaping roadmap priorities so the platform serves the whole business.
- Harden data quality. Schema validation that quarantines bad records without interrupting scheduled refreshes, plus freshness and critical-service audits with named owners.
- Run platform operations. On-call, monitoring, alerting, incident triage, and root-cause follow-through.
- Enable self-service. Documentation, semantic consistency, and BI access so partners can answer their own questions.
- Automate operational work. Extend the AI-assisted workflows already running in production for alert triage, refresh requests, and file processing.
What We’re Looking For:
- 2+ years managing engineers. Hiring, performance, and career development on a data or analytics engineering team. Prior management experience is expected, though we will consider lead engineers who have owned technical direction and developed the engineers around them.
- Advanced SQL and dimensional modeling. You have modeled a business domain for consumers with competing needs and kept it consistent as requirements changed.
- Deep dbt experience. You have owned a repository under version control with testing, PR review, CI, and change control, and you set that standard rather than working within one.
- Pipeline engineering. Python and cloud data infrastructure. We run on AWS with Glue, Step Functions, Lambda, and CDK.
- Reliability ownership. You have run on-call for a data platform, built alerting that teams trust, and led incident response.
- Analytical partnership. You’ve supported analysts, data scientists, or quantitative teams, and can translate a business question into a data model.
- Clear written communication. Architecture proposals, incident reviews, and candid tradeoff summaries for partners with different priorities.
- Prioritization judgment. You prioritize deliberately across many requests and communicate the tradeoffs clearly.
- Bonus: actuarial, risk, or fraud analytics; warranty, insurance, or service-contract programs; financial and revenue reporting; privacy and deletion compliance at scale; BI administration; or AI-assisted engineering workflows.
Expected Pay Range: $165,000 - $195,000 per year salaried*
*The target base salary range for this position is listed above. Individual salaries are determined based on a number of factors including, but not limited to, job-related knowledge, skills and experience.
Extend does not provide immigration-related sponsorship for this role.
Life at Extend:
- Working with a great team from diverse backgrounds in a collaborative and supportive environment.
- Competitive salary based on experience, with full medical and dental & vision benefits.
- Stock in an early-stage startup growing quickly.
- Generous, flexible paid time off policy.
- 401(k) with Financial Guidance from Morgan Stanley.
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