Data 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

In our day-to-day work, we design and maintain reliable data pipelines using Python and modern orchestration frameworks to move and transform raw data from a variety of sources. This includes working with APIs, event streams, and databases to ingest and process data at scale. We implement and maintain models, manage complex data transformations, and collaborate closely with other teams to ensure that the right data is available at the right time. Whether we're tuning a performance, debugging a transformation step, or shipping an AI-driven feature, every day is a chance to build something impactful.

What Will Make You Stand Out?

• Strong proficiency building data pipelines and managing data warehouses (2+ years)
• Working knowledge of Python for data extraction, processing and automation tasks.
• Experience with event tracking and NoSQL databases.
• Experience with dbt or similar tools.
• 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