Job description
[ Quora is a privately held, “remote-first” company . This position can be performed remotely from multiple countries around the world. Please visit careers.quora.com/eligible-countries for details regarding employment eligibility by country.]
About Quora:
Quora’s mission is to grow and share the world’s knowledge. To do so, we have two knowledge sharing products:
Quora: a global knowledge sharing platform with over 400M monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others.
Poe: a platform providing millions of global users with one place to chat, explore and build with a wide variety of AI language models (bots), including GPT-5, Claude 4.1, Grok 4, Veo 3 and more. As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and utilize these new models.
Behind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world.
This role will be working on our Quora product.
About the Team and Role:
Our data infrastructure team is responsible for all things data - data lake, data pipelines, distributed query engines, experimentation framework, data dashboards and visualization tools and so on. Our data-ecosystems is composed of open source technologies like Kafka, Hive, Trino, Spark and Airflow, along with a few in-house-built systems. As a member of our team you would spend time designing and scaling our existing infrastructure, improving system’s reliability, working closely with other teams to improve or create new tooling for our infrastructure, and promoting the correct use of data at the company. We are looking for someone who will be excited by the prospect of optimizing, enhancing or even re-designing our company’s data architecture/pipelines to support our next generation data initiatives.
🌟 Discover Our Team’s Exciting Projects! 🌟
Join us on a journey through some of our standout achievements that showcase innovation and collaboration at Quora:
🚀 Migrating a Decade of Redshift Usages to Trino at Quora: Dive into how we transformed our data ecosystem, enhancing efficiency and performance!
⚡ Revamping the Spark Ecosystem at Quora: Explore our efforts to elevate Spark, making it more powerful and user-friendly for our engineering teams!
🎥 Adopting Trino’s Fault-tolerant Execution Mode at Trino Summit 2023: Catch the highlights from our presentation at the Trino Summit, where we shared insights on building resilience in data processing!
Get inspired by the impact we’re making, and imagine the possibilities for your own journey with us!
Responsibilities:
Design and implement scalable and efficient data architectures, meeting data needs from data scientists, engineers and business partners
Identify and implement improvements to system’s cost efficiency, reducing data storage and processing costs
Bring your expertise to help model structured & unstructured data. Own these data models at a high level & be a data consultant for partner teams
Champion best practices on system usages and hold high-quality code standards
Participate in the team’s oncall rotation, helping solve timely reliability incidents
Minimum Requirements:
Availability for meetings and impromptu communication during Quora’s “ coordination hours ” (Mon-Fri: 9am-3pm Pacific Time)
Must have 4+ years of experience working in Data Infrastructure
Flexibility for working and owning different Data Engineering systems. Open to working on the areas with highest priority for the company at a given time
Operational mindset with ability to do Problem diagnosis, Root cause analysis, Performance tuning and Incident Management
Proficiency in Python and SQL query design
Proficiency with big data processing frameworks, like: Hive, Spark and Trino
Experience building data-intensive applications (high velocity/high volume)
Experience with SQL/NoSQL data store & data lake operations
Preferred Requirements:
Hands-on experience with AWS technologies like S3, EC2, RDS, EKS, or in Apache Iceberg
Flexible and positive team player with good interpersonal skills
At Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture.
Additional Information:
We are accepting applications on an ongoing basis. This role is a backfill for an existing vacancy.
Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary. For more information on benefits, visit this link: https://www.careers.quora.com/benefits
There are many factors that will determine the starting pay, including but not limited to experience, location, education, and business needs.
US candidates only: For US based applicants, the salary range is $155,656 - $225,160 USD + equity + benefits.
Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $201,613 - $233,311 CAD + equity + benefits. For all other locations in Canada, the salary range is $188,172 - $217,757 CAD + equity + benefits.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Please note: AI technology may assist in sorting applications and recording interview notes, but all decisions are made by a member of our team.
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