工程经理-人才分析
Engineering Manager-People Analytics
[**员工申请者隐私通知**](https://www.sofi.com/sofi-employee-applicant-privacy-notice/)
**我们是谁：**
与我们一同塑造更美好的财务未来。
与我们的会员一起，我们正在改变人们思考和与个人财务互动的方式。
我们是一家新一代的金融服务公司和国家银行，利用创新的、以移动优先的技术，帮助数百万会员实现他们的目标。行业正在经历前所未有的变革，而我们正处于最前沿。我们自豪地每天来到工作岗位，因为我们知道我们的工作对人们的生活有直接影响，我们的核心价值观始终指引着我们每一步。**加入我们，投资你自己、你的职业生涯和金融世界。**
##### **职位概述：**
该职位将领导支持人员分析的数据工程职能，包括在Snowflake上的AI辅助劳动力分析。这是一个需要亲自参与技术领导力以及人员领导力的球员教练角色，需要具备强大的业务合作能力，并能够平衡速度、质量、治理和创新。
#### **你将负责：**
**管理和发展数据工程师**
- 管理、指导并培养一支数据工程师团队。
- 设定对质量、协作、交付和技术所有权的期望。
- 建立一种强大的工程文化，让团队成员解决难题、快速行动并享受工作。
- 与其他数据工程师、人员分析师、数据科学家和业务利益相关者等跨职能团队合作，将需求转化为可投入生产的交付成果，并向非技术人员传达技术权衡。
**保持亲力亲为**
- 编写和审查生产代码。
- 主导设计评审、代码评审和技术问题解决。
- 在需要时进入关键的数据流程、模型或AI工作流。
**构建可扩展的人员数据基础**
- 设计和维护可持续的数据模型、数据流程、语义层和测试框架。
- 建立团队文档、数据血缘、数据质量和可观测性的实践。
**负责工程标准**
- 制定SQL、Python、dbt、Airflow、Snowflake、测试、文档、CI/CD和发布管理的标准。
- 确保团队交付的工作可靠、可维护、安全且易于理解。
- 执行数据治理政策和实践，以保持数据完整性、安全性和符合相关法规。
**支持AI驱动的分析**
查看英文原文
[**Employee Applicant Privacy Notice**](https://www.sofi.com/sofi-employee-applicant-privacy-notice/)
**Who we are:**
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. **Join us to invest in yourself, your career, and the financial world.**
##### **Role Summary:**
This role will lead the data engineering function supporting People Analytics, including AI-assisted workforce analytics on Snowflake. This is a player-coach role requiring hands-on technical leadership plus people leadership, with strong business partnership and the ability to balance speed, quality, governance, and innovation.
#### **What you’ll do:**
**Manage and develop data engineers**
- Manage, coach, and grow a team of data engineers.
- Set expectations for quality, collaboration, delivery, and technical ownership.
- Create a strong engineering culture where people solve hard problems, move quickly, and enjoy the work.
- Collaborate with cross-functional teams, such as other data engineers, people analysts, data scientists, and business stakeholders, to translate requirements into production-ready deliverables, and communicate technical trade-offs to non-technical partners.
**Stay hands on**
- Write and review production code.
- Lead design reviews, code reviews, and technical problem solving.
- Step into critical pipelines, models, or AI workflows when needed.
**Build scalable People data foundations**
- Design and maintain sustainable data models, pipelines, semantic layers, and testing frameworks.
- Establish team practices for documentation, lineage, data quality, and observability.
**Own engineering standards**
- Set standards for SQL, Python, dbt, Airflow, Snowflake, testing, documentation, CI/CD, and release management.
- Ensure the team ships work that is reliable, maintainable, secure, and understandable.
- Enforce data governance policies and practices to maintain data integrity, security, and compliance with relevant regulations.
**Support AI enabled analytics**
- Own technical delivery for AI-assisted workforce analytics and internal tools.
- Translate business needs into scalable technical designs, delivery plans, and engineering milestones.
- Partner with People Analytics, People leaders, Legal, Compliance, and other stakeholders to deliver trusted workforce insights.
- Partner on semantic models, evaluation datasets, testing, and quality controls for AI-assisted analytics
**Balance speed and rigor**
- Create enough process to protect quality, privacy, and trust for sensitive People data without slowing the team unnecessarily.
**What you’ll need:**
- A bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
- 7+ years in data engineering, analytics engineering, or data platform engineering.
- 5+ years managing or formally leading engineers.
- Proficiency in data engineering tech stack: Python / SQL / dbt / Airflow / Gitlab .
- Experience designing dimensional models, semantic layers, data marts, or analytical data products.
- Experience with data quality, testing, lineage, observability, and production support.
- Strong ability to translate business needs into technical architecture.
- Experience with sensitive or regulated data and access controls.
- Proven ability to coach engineers and build healthy technical culture
- Strong communication with technical and non technical stakeholders
- Proficiency in relational and cloud database platforms such as Snowflake, Redshift, or GCP.
- Thorough knowledge of data modeling, database design, data architecture principles, data operations, and CI/CD.
- Strong analytical and problem-solving abilities, with the capability to simplify complex issues into actionable plans.
**Preferred Experience**
- People analytics, HR data, compensation, talent, workforce planning, or Workday experience
- Experience building AI, LLM, RAG, or natural language analytics products
- Experience with Snowflake Cortex AI, Streamlit, semantic models, or evaluation frameworks
- Experience in fintech, banking, or regulated environments
**Compensation and Benefits**
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.
To view all of our comprehensive and competitive benefits, visit our **[Benefits at SoFi](https://sofietyinfo.sofi.com/sofi-benefits)** page!
##### SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
##### The Company hires the best qualified candidate for the job, without regard to protected characteristics.
##### Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
##### [New York applicants: Notice of Employee Rights](https://dol.ny.gov/system/files/documents/2022/02/ls740_1.pdf)
##### SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email [accommodations@sofi.com.](mailto:accommodations@sofi.com)
##### We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time.
**Internal Employees**
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.