Senior Analytics Engineer

For many of us there’s that one podcast we never miss, and video content is part of our daily routine, whether it’s professional or personal. But how many of us truly understand the effort that goes on behind the scenes? Here at Riverside, we know it well. That’s exactly why we built an AI-powered platform that helps content creators, podcasters, marketeers, and more at major brands like Netflix, Disney, Google, and Microsoft to create high-quality content with ease.

Riverside’s technology streamlines the entire content creation process, turning ideas into professional-grade content with the highest production standards, without requiring expensive equipment or external services. The secret? AI-driven tools that replace traditional production roles like editing, directing, and design, automating the entire process at the click of a button.

About The Data Team

Riverside’s Data & Analytics team believes there’s a better way to make data useful than just creating endless dashboards. We focus on in-depth analysis and building scalable, trustworthy data solutions that help every team make faster, smarter decisions. From analytics and business intelligence to data pipelines and predictive models, we turn raw information into real impact. If you’re passionate about finding radical new ways to leverage data, you’ll fit right in.

On your day to day

On a day-to-day basis, we transform raw data into clean, structured models using tools like SQL, Python, and dbt. We build and maintain modern BI platforms, develop reporting systems, and design AI-driven analytics that surface valuable insights quickly and reliably. Our team is hands-on with building reusable metrics, defining source-of-truth data models, and ensuring consistency through a strong semantic layer. Whether we’re shipping a new dashboard, debugging a dbt model, or refining how a metric is defined across the business, our focus is always on clarity, scalability, and enabling smarter, faster decisions.

What Will Make You Stand Out?

• Strong proficiency in SQL with hands-on experience building data pipelines (4+ years)
• Experience with modeling data using dbt or similar tools.
• Proficiency in Python
• Solid grasp of software engineering best practices, including query optimization, version control (e.g. Git), code reviews, and documentation.
• Analytical mindset with strong problem-solving skills, the ability to manage multiple priorities independently and a proactive approach to improving data processes and tools.
• Comfortable in a fast-paced, cross-functional environment; able to collaborate with teams across Product, BizOps, and Marketing.