Filmhub is a global, all rights, film & TV distributor. Leveraging decades of industry expertise and a legacy of billions of dollars in global box office, we distribute unlimited opportunity to the storytellers, creatives, and makers who drive our industry. Filmhub was founded by world-renowned composer and producer Klaus Badelt (Pirates of the Caribbean, Gladiator) and Silicon Valley entrepreneur Alan d’Escragnolle (Square, Intuit) and funded by the top investors in tech & entertainment including a16z & 8VC. Pairing a global network of strategic relationships with cutting-edge technology, we represent the industry’s leaders, from producers of global blockbusters to Oscar legends, festival darlings, cinema auteurs, and indie heroes.
What's the opportunity? 🤔
Filmhub is growing rapidly, and with that growth comes a need to unify and leverage data across every part of the business—from engineering and product to operations, content, and marketing. We’re looking for an
Analytics Engineer to design, build, and maintain our data infrastructure, create real-time visibility into key metrics, and drive actionable insights that help us scale.
This role exists to create clarity, visibility, and alignment around the metrics that matter most, and to make high-quality data easily accessible across teams. Success is a real-time, unified view of our business that empowers better decisions and faster growth.
This is a hybrid role for someone
based in Los Angeles—you’ll work remotely most of the time, but join our Head of Product Engineering in person a few days each week for hands-on collaboration, whiteboard deep dives, architecture discussions, and fast-paced product brainstorming where some of our best ideas take shape.
What big questions will I answer? 💡
- How can we make data easily accessible and actionable across teams, from engineering to marketing to ops?
- What should our key metrics be—and how can we track them consistently and in real time?
- Where can we enrich existing data, unify systems, and automate reporting to save time and drive decision making?
- How can we create a single source of truth that reflects the real performance of our company across departments, and their progress towards strategic goals?
- What opportunities are we missing in our current data ecosystem—and how can we close those gaps, what needs to be built, how do teams need to be supported and what needs to change?
What will I be doing? 🚀
In the next 12-18 months you will:
- Build and maintain pipelines to integrate data across key systems (e.g., app data, HubSpot, Plausible, business ops tools)
- Create dashboards, reports, and self-serve tools to give each team real-time access to metrics that matter
- Collaborate closely with engineering to understand application data, plan for upcoming features, and ensure integrations are accurate
- Define, refine, and document key metrics at all levels: company-wide (North Stars), department-level (Operator metrics), and individual-level
- Design and iterate on a scalable company-wide data model with domain-specific layers for business functions
- Lead the creation of data documentation and definitions to ensure clarity and consistency across the org
- Analyze data across multiple dimensions to identify insights, patterns, and areas for improvement
- Build “Gold” tables and structured data layers to support deep analysis and cross-functional conversations
- Build forecasting models across royalties, subscriptions, and AVOD/SVOD performance—spanning both B2B and B2C segments, leveraging machine learning where appropriate
- Develop and refine machine learning models for producer scoring, advanced title evaluation, channel health (blending asset count with revenue per title), and QC automation
- Partner with stakeholders to map processes and prioritize data needs by impact
- Advocate for more data capture and smarter data use within business processes
What skills do I need? 📖
- Strong experience in building and maintaining data pipelines and integrations (SQL, APIs, ETL tools, etc.)
- Experience unifying and modeling data across multiple systems and domains
- Ability to build clear, compelling dashboards and reports for technical and non-technical users alike
- Deep comfort working with stakeholders to define metrics and surface insights
- Familiarity with tools like dbt, Looker, Metabase, or similar
- Strategic thinker who can zoom out to define North Star metrics, and zoom in to identify process improvements
- Passion for creating clarity and transparency through data
- Comfort working independently and proactively in a fast-paced, startup environment
How can I stand out? 📣
- You’ve built data systems from the ground up—especially in fast-growing startups with evolving product and business models
- You love turning messy, siloed data into clean, actionable insights
- You have strong opinions on metrics—but you’re collaborative and flexible in how they’re implemented
- You’re just as comfortable writing SQL as you are whiteboarding metric logic with a cross-functional team, or building integrations and databases
- You’ve worked closely with both engineering and business teams, and you know how to bridge that gap
- You’re always looking for what’s missing—and you love filling in the blanks
At Filmhub, we take a transparent, structured approach to compensation. Offers are based on market data, your experience, location, and how the role fits within our leveling framework. Compensation includes base salary, equity, and benefits, with clear opportunities for growth. We make our entire compensation philosophy, levels, and salary ranges available for anyone to view—because we believe transparency builds trust. Learn more about how we approach compensation.
Filmhub, Inc. is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All applicants will be considered for employment without attention to age, race, color, religion, gender, sexual orientation, gender identity, national origin, veteran, or disability status. We will not tolerate discrimination or harassment based on any of these characteristics.
