Data Engineer II

Summary

Join Scribd's ML Data Engineering team as a Software Engineer II and contribute to building and optimizing large-scale data processing systems. You will design, develop, and maintain data pipelines for metadata extraction and enrichment, working with diverse datasets and collaborating with cross-functional teams. The role requires proficiency in data engineering, software development, and scalable systems, along with experience with technologies like Python, Spark, and AWS. Scribd offers a competitive compensation package, including a comprehensive benefits package and flexible work arrangements through Scribd Flex, requiring occasional in-person attendance. The company values a culture of GRIT, emphasizing goal setting, results achievement, innovation, and teamwork. Scribd is committed to equal employment opportunity and encourages applications from diverse backgrounds.

Requirements

• 5+ years of experience as a professional software engineer (post qualifications)
• Proficient in one or more programming languages, such as Python, Ruby, Scala, or similar
• Hands-on experience with real-time data processing
• Experience in frameworks like Apache Spark, Databricks, or similar tools for large-scale data processing
• Experience working with systems at scale
• Experience maintaining and deploying infrastructure on public cloud provider (AWS, Azure, or Google Cloud)
• Hands-on experience with building, deploying, and optimizing solutions using ECS, EKS or AWS Lambdas
• Proven ability to test and optimize systems for performance and scalability
• Bachelor’s in CS or equivalent professional experience

Responsibilities

• 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

Preferred Qualifications

Bonus points if you have experience working with Machine Learning systems

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
• Onboarding stipend for home office peripherals + accessories
• 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 Employee Resource Groups and programs that foster an inclusive and diverse workplace