Sr. Analytics Engineer

Philo: a streaming service for TV and movie loversAt Philo, we're a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented — in short, we're building the TV experience that we've always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences.Data at PhiloData underpins everything we do at Philo: making informed business decisions; analyzing and improving the quality of our streaming experience; running product experiments to optimize our signup flows and improve user journeys; and making it effortless for our users to find the perfect thing to watch. Philo serves over a billion streams to its users every year, generating a wealth of data that we leverage at all levels of the organization. Philo's data platform operates at a very large scale, processing trillions of events annually in a petabyte-scale data lake and supporting thousands of data workflows and analytical queries that power decision-making across the company.Philo's Data Engineering team encompasses both data engineering and analytics engineering. As an analytics engineer at Philo, you'll own the data modeling layer that turns raw event and application data into the clean, trusted data products the entire company relies on — from metric definitions and dimensional models to the governed semantic layer that ensures everyone is looking at the same numbers. You'll work closely with data scientists, analysts, and business stakeholders across the organization to understand their analytical needs and translate them into well-modeled, well-documented, and performant data products in dbt and Snowflake.We are passionate about providing a high-quality, trustworthy data platform for the entire company, using both cutting-edge technologies and proven engineering practices in close collaboration with every department. Our analytics engineering stack centers on dbt and Snowflake, supported by tools like Segment, Avo, and BigEye for event tracking, data quality, and observability.Some of the recent projects that analytics engineers at Philo have worked on include building new models for key financial data, dbt model design and refactoring, metric definition and governance, per-query cost optimization in Snowflake, and developing data quality testing and documentation frameworks.The RoleWe're looking for a Senior Analytics Engineer to own and elevate the data modeling layer that powers decision-making across Philo. In this role, you'll be the person who transforms raw, messy application and event data into clean, trusted, well-documented data products that the entire company relies on. You'll design and maintain dimensional models, define and govern key business metrics, and ensure semantic consistency across our data stack — so that when someone asks "what does this number mean?", there's always a clear, reliable answer.This is a high-impact IC role: you'll partner directly with stakeholders across Finance, Product, Marketing, Ad Sales, and Engineering to deeply understand their analytical needs and translate them into scalable, performant dbt models and data products. You'll also work closely with the data engineering side of the team to ensure the underlying infrastructure supports your modeling work, and with analysts and data scientists to make sure the data you deliver is easy to use, well-tested, and trustworthy.The ideal candidate has strong opinions about how analytics engineering should be done — how to structure a dbt project, when to denormalize, how to manage slowly changing dimensions, how to build a metric layer that people actually trust — and the experience to back those opinions up.Responsibilities:Design, build, and maintain Philo's core dimensional models and data marts in dbt, serving as an owner of the analytics engineering layer of our data stackDefine and govern key business metrics and KPIs, ensuring consistent definitions and reliable calculations across all downstream reporting and analyticsPartner with stakeholders across the organization (Finance, Product, Marketing, Ad Sales, Content, and others) to understand their data needs and translate business questions into well-modeled, performant data productsEstablish and enforce best practices for dbt project structure, model design patterns, documentation, and testing — raising the quality bar for analytics engineering at PhiloBuild and maintain comprehensive data documentation and a data catalog so that analysts, data scientists, and business users can confidently self-serveImplement and maintain data quality checks and monitoring (e.g., via dbt tests, BigEye, or similar tools) to proactively catch issues bef