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Robinhood
Robinhood

Democratizing finance for all.

Analytics Engineer

职能数据分析
级别中级
地点Menlo Park, CA; Toronto, Canada
方式现场办公
类型全职
发布2个月前

薪酬

$145,000 - $170,000

立即申请

福利待遇

医疗保险

401k

股权

育儿假

心理健康支持

Learning Budget

必备技能

SQL

Python

Apache Spark

ETL

Data modeling

Dashboard development

Git

CI/CD

Join us in building the future of finance.

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About the team + role

Robinhood’s

Analytics Engineering team, part of the Data Science organization, is the backbone of our decision-making ecosystem. We design and deliver foundational data products

that power everything from product innovation to regulatory compliance and operational excellence. Our mission is simple but ambitious: enable every team at Robinhood to access trustworthy, scalable, and self-serve analytics—so the right decisions happen faster.

We operate at the intersection of data engineering, data science, and product strategy, collaborating closely with product managers, engineers, and data scientists to transform raw data into clear, actionable intelligence.

As an Analytics Engineer, you will be a key architect of Robinhood’s data foundation. You’ll own the design and development of high-performance ETL pipelines, data models, and analytics tools that fuel critical decisions across the company. Your work will directly influence product strategy, regulatory reporting, and operational efficiency, ensuring Robinhood remains agile and data-driven at scale.

This is more than a build role—you’ll help define metrics, shape datasets, and set the standards for analytics excellence across the company. The systems and frameworks you create will have a long-lasting impact on Robinhood’s growth trajectory.

This role is based in our Toronto, ON office(s), with in-person attendance expected at least 3 days per week.

What you’ll do

Partner cross-functionally with product, engineering, and data science teams to scope and deliver high-impact analytics initiatives, from metric definitions to fully automated reporting solutions.

  • Design and maintain reliable, scalable ETL pipelines and data models using modern data tools (e.g., Airflow, Spark), ensuring performance and accuracy at scale.

  • Lead end-to-end development of analytics products—from ingestion to visualization—that meet mission-critical business, product, and regulatory needs.
    Build internal frameworks and tooling to make high-quality data more accessible and actionable across the organization.

  • Collaborate with data scientists to transform raw data into meaningful insights that directly shape business and product outcomes.
    Champion analytics best practices and drive a culture of data literacy, empowering teams to confidently explore and interpret data on their own.

What you bring

  • 3+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field.

  • Strong expertise in advanced SQL, Python scripting, and Apache Spark (Py Spark, Spark SQL) for data processing and transformation.

  • Proficiency in building, maintaining, and optimizing ETL pipelines, using modern tools like Airflow or similar.

  • Experience in building polished and performant dashboards using tools like Superset, Looker, Tableau.

  • Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.

  • A strong product approach.

  • Ability to work in a fast-paced, and highly cross-functional environment.

Bonus points:

  • Data Engineering experience

  • Familiarity with HR systems like Greenhouse, Workday, and One Model

  • Passion for working and learning in a fast-growing company

  • Intense sense of curiosity

  • Satisfaction from mentoring and encouraging others in your field

Our team is committed to providing an inclusive and welcoming interview experience for all candidates. If you require a specific accommodation during the application or interview process due to a physical or mental condition, please complete this Applicant Accommodation Form to notify our team. The form should only be completed if you need a specific accommodation.

In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits.
Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed.

Base Pay Range:

Toronto, ON**$145,000—$170,000 CAD**

Click here to learn more about our Total Rewards, which vary by region and entity.

If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.

Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.

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关于Robinhood

Robinhood

Robinhood

Public

Democratizing finance for all.

1,001-5,000

员工数

Menlo Park

总部位置

$32B

企业估值

评价

10条评价

3.7

10条评价

工作生活平衡

3.2

薪酬

3.5

企业文化

4.1

职业发展

3.0

管理层

2.8

65%

推荐率

优点

Great team culture and collaborative environment

Flexible hours and work-life balance

Innovative projects and cutting-edge technology

缺点

Management issues and lack of direction

High pressure and stressful environment

Long hours and overwhelming workload

薪资范围

42个数据点

Junior/L3

Senior/L5

Junior/L3 · Risk Data Scientist

1份报告

$144,069

年薪总额

基本工资

$110,822

股票

-

奖金

-

$144,069

$144,069

面试评价

4条评价

难度

3.5

/ 5

时长

21-35周

体验

正面 0%

中性 50%

负面 50%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience