数据工程师负责人
Lead Data Engineer
关于Atticus
任何时候,都有1600万美国人正经历需要紧急法律系统或政府帮助的危机。正确的援助可以改变他们的生活。但如今,大多数人从未获得过这种帮助。
Atticus让任何生病或受伤的美国人轻松获得改变人生的援助。我们的使命是拆除人们与应得援助之间的障碍。在过去的六年里,我们已成为连接残障人士与政府福利的领先平台。
我们还帮助事故、不当行为和暴力的受害者从保险公司获得赔偿。到目前为止,我们已帮助数十万人获得超过100亿美元的改变人生的援助——并获得了20000多条五星评价。而我们才刚刚开始。
我们从Fika、Forerunner、Google Ventures和True Ventures等顶级风险投资公司筹集了超过1亿美元的资金,正在打造一个定义新类别的企业,帮助有需要的美国人。
职位
我们正在寻找第一位内部数据工程师,负责并推动核心数据基础设施的发展。这是一个早期且影响深远的职位。随着工程团队下数据工程职能的成长,你将真正参与塑造其构建方式——流程、标准和团队文化。
你将处于工程团队和业务运营团队的交汇点,这意味着你将同时花时间构建可靠、可扩展的系统,并将业务需求转化为设计良好的数据产品。你将与数据科学家、业务分析师和产品负责人紧密合作,确保我们的数据干净、可访问且值得信赖。
你将负责管理我们的数据仓库、管道和转换层
设计、构建和维护可扩展、可靠的数据显示管道,从我们平台和第三方来源获取数据,确保下游消费者始终能获得可用且可信的数据
与数据科学家和分析师合作,提供干净、文档齐全的数据集并优化查询性能,使团队减少处理数据的时间,更多地生成洞察
逐步改进和现代化我们的现有数据系统——你不会从零开始构建一切,但你会知道如何评估我们现有的系统,优先考虑重要的部分,并谨慎地进行迁移
实施数据质量监控、警报和文档实践,以在整个组织中建立信任
这个职位是一个难得的机会,加入一家快速增长的C轮融资初创公司
查看英文原文
About AtticusAt any given time, 16 million Americans are experiencing a crisis that requires urgent help from our legal system or government. The right assistance could transform their lives. But today, most never get it.Atticus makes it easy for any sick or injured American to get life-changing aid. Our mission is to tear down barriers between people in crisis and the aid they deserve. In the last six years, we’ve become the leading platform connecting people with disabilities to government benefits.We also help victims of accidents, misconduct, and violence get compensation from insurance. So far, we’ve helped hundreds of thousands of people access over $10 billion in life-changing aid —and earned over 20,000 five-star reviews. And we’re just getting started.We've raised more than $100 million from top VC firms like Fika, Forerunner, Google Ventures, and True Ventures, and we’re on our way to creating a category defining business assisting needy Americans.The JobWe are looking for our first in-house Data Engineer to own and evolve our core data infrastructure. This is an early and high-impact role. As the data engineering function grows under Engineering, you'll have a real voice in shaping how it's built - the processes, standards, and team culture.You'll sit at the intersection of our Engineering and Business Operations teams, which means you'll spend your time both building reliable, scalable systems and translating business needs into well-designed data products. You'll work closely with data scientists, business analysts, and product leaders to make sure our data is clean, accessible, and trustworthy.What You'll DoOwn and operate our data warehouse, pipelines, and transformation layerDesign, build, and maintain scalable, reliable data pipelines that ingest data from across our platform and third-party sources, ensuring data is always available and trustworthy for downstream consumersPartner with data scientists and analysts to deliver clean, well-documented datasets and optimize query performance so teams spend less time wrangling data and more time generating insightsIncrementally improve and modernize our existing data systems - you won't build everything from scratch, but you'll know how to assess what we have, prioritize what matters, and migrate thoughtfullyImplement data quality monitoring, alerting, and documentation practices that build trust across the organizationThe role is a rare opportunity to join a fast-growing Series C startup that doubles as a B-corp social enterprise. Every project you take on will help clients in need get the help they deserve, and you’ll shape our company culture as we scale. We’re looking for data scientists who are excited about our mission and the challenges it entails.QualificationsRequired:4+ years of professional experience in data engineering, ideally at a high-growth startup or fast-moving team within a larger organizationHands-on experience with the modern data stack - proficiency with BigQuery (or a comparable cloud warehouse), dbt, and an orchestration tool like Dagster or AirflowStrong SQL skills and fluency in Golang, Python, or another common Data Engineering languageTrack record of improving or modernizing data systems iteratively - you're comfortable inheriting legacy infrastructure and systems and making them progressively betterStrong communication and collaboration skills - able to work fluidly across both technical and business-oriented teamsBonus / Nice-to-Have:Experience transitioning data infrastructure from an outsourced or contractor model to an in-house teamFamiliarity with data observability toolsExperience supporting or collaborating with a data science function, including ML feature pipelinesWe are strongly committed to building a diverse team. If you’re from a background that’s underrepresented in tech, we’d love to meet you.Salary and BenefitsThis is a rare opportunity to join a startup that has strong traction (substantial funding, well-respected backers, tremendous growth, and many happy customers) but is still small enough that you can have a huge impact and play a role in shaping our culture.We're a certified B Corporation tackling a critical social problem. Our mission to help people in need drives everything we do, and your work here will touch many lives.We offer competitive pay—including equity for all employees —and generous benefits:Medical and dental insurance with 100% of premiums covered for employees and their families15 vacation days & ~20 paid holidays each year (including two weeks at end-of-year)Free membership to OneMedical$600/year internet stipend$1,000/year reimbursable stipend for education and training outside of workUp to $1,200/year student loan repayment assistance401(k) and optional HSA/FSAWe anticipate the base salary band for this role will be between $174,000 and $230,000 in addition to equity and benefits. The salary at offer will be determined by a number of factors such as candidate's experience, knowledge, skills and abilities, as well as internal equity among our team.LocationThis job is fully remote and we're committed to empowering everyone with flexibility. Work remotely, and travel to LA (on the company dime) as needed to be with your colleagues – usually quarterly, plus offsites. We care a lot about building a great culture and we think some interactions need to happen in person, so we put a lot of thought into retreats, offsites, and other ways to gather.