Rent The Runway
Rent the Runway (RTR) is transforming the way we get dressed by pioneering the world’s first Closet in the Cloud. Founded in 2009, RTR has disrupted the $2.4 trillion fashion industry by inspiring women with a more joyful, sustainable and financially‑savvy way to feel their best every day. As the ultimate destination for circular fashion, the brand now offers infinite points of access to its shared closet via a fully customizable subscription to fashion, one‑time rental or ownership. RTR offers designer apparel and accessories from hundreds of brand partners and has built in‑house proprietary technology and a one‑of‑a‑kind reverse logistics operation. Under CEO and Co‑Founder Jennifer Hyman’s leadership, RTR has been named to CNBC’s “Disruptor 50” five times in ten years, and has been placed on Fast Company’s Most Innovative Companies list multiple times, while Hyman herself has been named to the “TIME 100” most influential people in the world and as one of People magazine’s “Women Changing the World.”
About the Team Data is core to RTR’s strategy and is embedded across product, logistics, customer experience, and business operations. The Data Analytics team is responsible for delivering accurate, scalable data to the organization, including core dbt models, data definitions, reporting foundations, insights, and self‑service analytics.
We are now establishing a dedicated Analytics Engineering function within the Data Analytics team to ensure our data models are scalable, maintainable, well‑governed, and aligned to the fast‑paced and evolving needs of the business.
About the Role We are seeking an Analytics Engineering Lead to take ownership of our core dbt data model, establish modeling best practices, and build the foundation of a scalable Analytics Engineering team. This role requires a strong individual contributor who is also capable of acting as a technical leader – defining architectural direction, reviewing and guiding contributions from analysts, and partnering closely with Data Engineering on ingestion, orchestration, and performance.
This is a hands‑on leadership role: you will assess the current model, identify areas to simplify and refactor, define a cohesive governance strategy, execute improvements directly, and build a roadmap to evolve the data model over time. As the function grows, this role will be involved in hiring and mentoring additional Analytics Engineers.
What You’ll Do
Own
the core dbt model: assess current architecture, identify bottlenecks, simplify complexity, and improve maintainability and performance.
Define
the technical strategy for the Analytics Engineering function, establishing modeling standards, version control norms, documentation frameworks, and code review practices.
Review PRs
from BI Analysts and guide contributions to ensure accuracy, performance, and adherence to modeling conventions.
Serve as the
primary bridge
between BI (analytics‑facing) and Data Engineering (ingestion, orchestration, infrastructure).
Partner with Data Engineering to improve pipeline reliability, testing coverage, data freshness, and orchestration flows.
Lead and execute
large‑scale refactors , including preparation for and/or execution of the migration from Snowflake to BigQuery.
Improve and enforce
data governance , including data quality checks, model ownership boundaries, and documentation.
Over time,
recruit, onboard, and mentor
additional Analytics Engineers to scale the function.
Operate with
high ownership and autonomy , driving both strategy and execution.
About you
5+ years owning dbt in production
– designing model architecture, testing, documentation, enforcing standards, and reviewing PRs.
7+ years working with analytical data models and large‑scale datasets
in modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift).
Expert in SQL
and in designing
data models that support Looker explores and self‑service analytics.
Comfortable working with large, high‑complexity dbt model
– with deep dependency graphs, layered logic, legacy components, and incremental refactoring needs.
Comfortable partnering with
Data Engineering
on ingestion,
orchestration
(Prefect), CI/CD, and data quality frameworks.
Experience defining and maintaining Git‑based development workflows
(branching strategy, PR review processes, testing gates, and controlled release/promotion).
Able to
simplify complex data environments
and make
scalable architecture decisions.
Strong communicator
who can influence across technical and non‑technical stakeholders.
Thrives in
high‑ownership, fast‑paced, iterative
environments.
Nice to Have
Looker / LookML
semantic modeling experience.
Experience with
event analytics and subscription lifecycle
data (e.g.,
Heap , Mixpanel, Segment).
Experience working in a
fast‑growing environment
where dbt models required refactoring for scale and maintainability.
Experience
leading or contributing to a data warehouse migration.
Python
for automation, testing, or internal tooling.
Benefits At Rent the Runway, we’re committed to the wellbeing of our employees and aim to create a workplace that fosters both personal and professional growth. Our inclusive benefits include, but are not limited to:
Paid Time Off including vacation, paid bereavement, and family sick leave.
Universal Paid Parental Leave for both parents + flexible return‑to‑work program.
Paid Sabbatical after 5 years of continuous service.
Exclusive employee subscription and rental discounts.
Comprehensive health, vision, dental, FSA and dependent care from day 1 of employment.
401(k) match.
Company‑wide events and outings.
Hybrid work – individual contributors on our tech team follow a sprint schedule and generally alternate fully remote weeks and working remotely two days per week, in accordance with Company policies.
Rent the Runway is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant or employee based on any legally-recognized basis, including, but not limited to: race, color, religion, sex (including pregnancy, lactation, childbirth or related medical conditions), sexual orientation, gender identity, age (40 and over), national origin or ancestry, citizenship status, physical or mental disability, genetic information (including testing and characteristics), veteran status, uniformed service member status or any other status protected by federal, state or local law.
The anticipated base salary for this position is $170k to $200k. The actual base salary offered will depend on a variety of factors, including but not limited to the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held.
#J-18808-Ljbffr
About the Team Data is core to RTR’s strategy and is embedded across product, logistics, customer experience, and business operations. The Data Analytics team is responsible for delivering accurate, scalable data to the organization, including core dbt models, data definitions, reporting foundations, insights, and self‑service analytics.
We are now establishing a dedicated Analytics Engineering function within the Data Analytics team to ensure our data models are scalable, maintainable, well‑governed, and aligned to the fast‑paced and evolving needs of the business.
About the Role We are seeking an Analytics Engineering Lead to take ownership of our core dbt data model, establish modeling best practices, and build the foundation of a scalable Analytics Engineering team. This role requires a strong individual contributor who is also capable of acting as a technical leader – defining architectural direction, reviewing and guiding contributions from analysts, and partnering closely with Data Engineering on ingestion, orchestration, and performance.
This is a hands‑on leadership role: you will assess the current model, identify areas to simplify and refactor, define a cohesive governance strategy, execute improvements directly, and build a roadmap to evolve the data model over time. As the function grows, this role will be involved in hiring and mentoring additional Analytics Engineers.
What You’ll Do
Own
the core dbt model: assess current architecture, identify bottlenecks, simplify complexity, and improve maintainability and performance.
Define
the technical strategy for the Analytics Engineering function, establishing modeling standards, version control norms, documentation frameworks, and code review practices.
Review PRs
from BI Analysts and guide contributions to ensure accuracy, performance, and adherence to modeling conventions.
Serve as the
primary bridge
between BI (analytics‑facing) and Data Engineering (ingestion, orchestration, infrastructure).
Partner with Data Engineering to improve pipeline reliability, testing coverage, data freshness, and orchestration flows.
Lead and execute
large‑scale refactors , including preparation for and/or execution of the migration from Snowflake to BigQuery.
Improve and enforce
data governance , including data quality checks, model ownership boundaries, and documentation.
Over time,
recruit, onboard, and mentor
additional Analytics Engineers to scale the function.
Operate with
high ownership and autonomy , driving both strategy and execution.
About you
5+ years owning dbt in production
– designing model architecture, testing, documentation, enforcing standards, and reviewing PRs.
7+ years working with analytical data models and large‑scale datasets
in modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift).
Expert in SQL
and in designing
data models that support Looker explores and self‑service analytics.
Comfortable working with large, high‑complexity dbt model
– with deep dependency graphs, layered logic, legacy components, and incremental refactoring needs.
Comfortable partnering with
Data Engineering
on ingestion,
orchestration
(Prefect), CI/CD, and data quality frameworks.
Experience defining and maintaining Git‑based development workflows
(branching strategy, PR review processes, testing gates, and controlled release/promotion).
Able to
simplify complex data environments
and make
scalable architecture decisions.
Strong communicator
who can influence across technical and non‑technical stakeholders.
Thrives in
high‑ownership, fast‑paced, iterative
environments.
Nice to Have
Looker / LookML
semantic modeling experience.
Experience with
event analytics and subscription lifecycle
data (e.g.,
Heap , Mixpanel, Segment).
Experience working in a
fast‑growing environment
where dbt models required refactoring for scale and maintainability.
Experience
leading or contributing to a data warehouse migration.
Python
for automation, testing, or internal tooling.
Benefits At Rent the Runway, we’re committed to the wellbeing of our employees and aim to create a workplace that fosters both personal and professional growth. Our inclusive benefits include, but are not limited to:
Paid Time Off including vacation, paid bereavement, and family sick leave.
Universal Paid Parental Leave for both parents + flexible return‑to‑work program.
Paid Sabbatical after 5 years of continuous service.
Exclusive employee subscription and rental discounts.
Comprehensive health, vision, dental, FSA and dependent care from day 1 of employment.
401(k) match.
Company‑wide events and outings.
Hybrid work – individual contributors on our tech team follow a sprint schedule and generally alternate fully remote weeks and working remotely two days per week, in accordance with Company policies.
Rent the Runway is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant or employee based on any legally-recognized basis, including, but not limited to: race, color, religion, sex (including pregnancy, lactation, childbirth or related medical conditions), sexual orientation, gender identity, age (40 and over), national origin or ancestry, citizenship status, physical or mental disability, genetic information (including testing and characteristics), veteran status, uniformed service member status or any other status protected by federal, state or local law.
The anticipated base salary for this position is $170k to $200k. The actual base salary offered will depend on a variety of factors, including but not limited to the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held.
#J-18808-Ljbffr