Analytics Engineer, Scribd

• You are a highly motivated and technically adept individual who thrives on solving complex data challenges and ambiguous business problems.
• You excel in our fast-paced and collaborative environment, leveraging your strong communication skills to effectively interact with data scientists, data engineers, executives, and cross-functional teams.
• Your strategic thinking allows you to balance high-level data architecture considerations with meticulous attention to detail in your code and data models
• Your natural curiosity drives you to explore intricate data systems, optimize query performance, and find innovative solutions to data pipeline challenges.
• You're excited about the intersection of data engineering and analytics, always seeking to bridge the gap between complex data systems and actionable business intelligence
• You have a knack for translating business requirements into robust data solutions, ensuring data accuracy, accessibility, and scalability.
• Your commitment to data quality and governance is evident in your consistent advocacy for and implementation of best practices in data modeling and engineering
• 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.

Desirable

• The mission of the business strategy & analytics team is to ensure the entire company understands business performance and trends, and to empower all business teams to make good decisions with data
• In this role, you will play a crucial part in transforming our vast amounts of data into actionable insights that drive key business decisions for our Discovery and User Generated (UGC) Pillars.
• You'll work at the intersection of data engineering, analytics and product owners focusing on creating accurate, efficient and scalable data models and tables that will power our analytics and machine learning initiatives.
• A key aspect of your role will be managing and ensuring correct data definitions across the organization, collaborating closely with business stakeholders to establish a common data language
• 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