Scribd is hiring a
Analytics Engineer

Summary

Join Scribd's team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare.

Requirements

• Proven experience (2+ years) in analytics engineering, business intelligence or quantitative data analysis, preferably in a high-velocity environment, with a track record of delivering accurate, efficient, scalable and well defined data models
• Highly analytical mindset with demonstrated ability to work through complex, ambiguous datasets
• Expert level proficiency in SQL with experience in data modeling
• Expertise in programming languages: Python and PySpark
• Strong proficiency in data visualization tools such as Tableau, Looker, or similar tools to create compelling dashboards and reports
• Self-motivated, proactive, and able to work effectively both independently and collaboratively in a dynamic, fast-paced environment
• Excellent communication skills, with the ability to convey complex issues and insights to both technical and non-technical stakeholders in a clear and actionable manner
• Strong problem-solving skills with the ability to think critically to ensure we are building ensuring accuracy and attention to detail
• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline. A Master's degree is a plus

Responsibilities

• Design, develop, and maintain advanced data models that support the Discovery and UGC pillars (e.g. impression tracking, document uploads, ads reporting, etc.)
• Collaborate closely with data scientists, analysts, product managers, and business stakeholders to understand complex business requirements and translate them into robust data solutions
• Create and optimize complex SQL queries and data transformations to support large-scale data analysis and reporting
• Collaborate with Data Engineers to implement, develop and maintain production data pipelines using our modern data stack
• Contribute to the development of our internal data platform, improving data accessibility and usability for the entire organization
• Create comprehensive documentation for data processes, models, and metrics to promote data literacy across the company
• Ensure data quality, accuracy, and consistency across all our data platforms, implementing data validation processes and monitoring 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
• 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