Software Engineer, Scribd

Python and Data pipelines

$103.5-196k

Salary dependent on US location. Canada: $131,500 CAD - $174,500 CAD + Competitive equity ownership for all locations

AWS

GCP

Python

Scala

Kafka

Sidekiq

Airflow

Ruby

Terraform

Azure

Spark

Kinesis

Sagemaker

Ruby on Rails

Datadog

Mid and Senior level

Remote in Canada, US

More information about location

E-book and audiobook subscription service

Be an early applicant

E-book and audiobook subscription service

201-500 employees

B2CLearningEntertainmentSocial

Be an early applicant

$103.5-196k

Salary dependent on US location. Canada: $131,500 CAD - $174,500 CAD + Competitive equity ownership for all locations

AWS

GCP

Python

Scala

Kafka

Sidekiq

Airflow

Ruby

Terraform

Azure

Spark

Kinesis

Sagemaker

Ruby on Rails

Datadog

Mid and Senior level

Remote in Canada, US

More information about location

201-500 employees

B2CLearningEntertainmentSocial

Company mission

To revolutionize the way the world reads and learns.

Job

Company

Role

Who you are

We are seeking a Software Engineer II with a strong background in data engineering, software development, and scalable systems
4+ years of experience in backend software engineering, with hands-on work in developing data pipelines and building and deploying your own infrastructure
Proficient in one or more programming languages, such as Python, Ruby or similar
Experience working with a public cloud provider (AWS, Azure, or Google Cloud)
Hands-on experience with building, deploying, and optimizing solutions using ECS, EKS or AWS Lambdas
Experience with queueing and streaming technologies like SQS, Sidekiq, Kafka or Kinesis
Experience working with systems at scale such as External APIs, and data transformations
Proven ability to test and optimize systems for performance and scalability
Bachelor’s in CS or equivalent professional experienceBonus points if you have experience working with Machine Learning systems

What the job involves

The ML Data Engineering team is at the heart of metadata extraction and enrichment for all of our brands, managing and processing hundreds of millions of documents, billions of images, and serving millions of users
We operate at an unparalleled scale, handling diverse datasets, including UGC documents, ebooks, audiobooks, and more. Our goal is to build robust systems that drive content discovery, trust, and structured metadata across our platforms
As part of the ML Data Engineering team, you will work on designing, building, and optimizing systems that extract, enrich, and process metadata at scale
You’ll collaborate closely with machine learning teams, product managers, and other engineers to ensure the smooth integration and processing of vast amounts of structured metadata
Our team uses various technologies. The following are the ones that we use on a regular basis: Python, Scala, Ruby on Rails, Airflow, Databricks, Spark, HTTP APIs, AWS (Lambda, ECS, SQS, ElastiCache, Sagemaker, Cloudwatch, Datadog) and Terraform
Design and develop data pipelines to extract, enrich, and process metadata from millions of documents, images, and other content types
Collaborate with cross-functional teams, including ML engineers and product managers, to deliver scalable, efficient, and reliable metadata solutions
Build and maintain systems that operate at a massive scale, handling hundreds of millions of documents and billions of images
Optimize and refactor existing systems for performance, scalability, and reliability
Ensure data accuracy, integrity, and quality through automated validation and monitoring
Participate in code reviews, ensuring best practices are followed and maintaining high-quality standards in the codebase
Manage and maintain data pipelines, security and infrastructure

Our take

The world's biggest site for social reading and publishing, Scribd's website has over 250 million unique visitors each month and a vast content library, consisting of over 200 million audiobooks, magazines, ebooks and newspapers as well as media created by the Scribd community.

While Scribd is the largest social reading site, it is not alone in offering this kind of media. It competes against some major players, the largest of which are Amazon's Kindle and Audible offerings, but also includes the likes of BookMate and the non-profit Internet Archive. Where it stands aside is in its feature-rich reader and the sheer diversity of its library, which, thanks to partnerships with several major publishers, features numerous popular titles as well as a range of independent creators.

Further differentiating it from competitors, the company taken a firm stand on social issues, in particular the recent wave of book bannings taking place across the United States. By making the banned titles freely available it hopes to do its part in preserving literary freedom. With this tendency showing no signs of slowing down, Scribd's intervention in this area could prove to be important.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

0% employee growth in 12 months

Glassdoor (2.5)

Trustpilot (1.3)

Company

Funding (last 2 of 7 rounds)

Nov 2019

$58m

LATE VC

Jan 2015

$22m

LATE VC

Total funding: $105.8m

Company benefits

Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Short-term/long-term disability plans
401k/RSP matching
Tuition Reimbursement
Learning & Development programs
Quarterly stipend for Wellness, Connectivity & Comfort
Mental Health support & resources
Free subscription to Scribd + gift memberships for friends & family
Referral Bonuses
Book Benefit
Sabbaticals
Company wide events
Team engagement budgets
Vacation & Personal Days
Paid Holidays (+ winter break)
Flexible Sick Time
Volunteer Day
Company-wide Diversity, Equity, & Inclusion programs

Company HQ

China Basin, San Francisco, CA

Leadership

Trip Adler

(CEO)

Having studied at Harvard until 2006, they co-founded Scribd in March 2017. They have worked as CEO ever since then.

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