Analytics Engineer 5 - Enterprise Data

The Enterprise Data Science & Engineering (DSE) team’s mission is to make Netflix technologists more productive and our enterprise data stronger and more connected. We achieve this through dedicated data products and deep partnerships that leverage our data expertise.

We are driving a major initiative to deepen data excellence across the organization. Our focus is on enabling high-quality data foundations that support next-generation tools and internal productivity products, ensuring our data ecosystem remains robust and scalable as the business grows.

We are looking for a Analytics Engineer to lead the analytics strategy for Data Health at Netflix.

This role leans heavily into analytics and strategy. While engineering skills are required to access and model data, the primary focus is on defining measurement frameworks. You will be a thought leader responsible for conceptualizing what "healthy data" looks like across diverse domains and translating abstract concepts like "trust," "availability," or "compliance" into concrete, actionable metrics.

As an Analytics Engineer, you will act as a cross functional lead, partnering with Engineering Leaders, Product Managers, and other DSE teams to establish comprehensive visibility into the state of Netflix’s data ecosystem.

What You Will Do

• Define Data Excellence Metrics: You will lead the development of advanced quality indicators, moving beyond standard availability checks to define complex measures of data health.

• Build the Analytical Foundation: Design and implement the data models and dashboards that will serve as the trusted source for understanding the health of our critical data assets. You will be responsible for visualizing the state of our data landscape for executive leadership.

• Drive Strategy through Insights: Use data to influence engineering behavior and investment. You will analyze trends in lineage, asset utilization, and data lifecycle to identify opportunities for high-impact improvements across Netflix.

• Partner on Platform Capabilities: Collaborate with Data Platform engineering teams to ensure our infrastructure and orchestration tools emit the necessary metadata and telemetry to support sophisticated health analysis.

• Connect the Dots: Work across domain-centric workstreams to standardize how we evaluate data quality, ensuring consistent definitions and standards apply across the company.

• Measure Impact: Develop metrics to track the success of our data initiatives, focusing on improvements in developer productivity, reduction in data friction, and the adoption of standardized tooling.

What We Are Looking For

• Analytical Leadership: You excel at defining metrics in complex spaces. You are adept at asking "what should the data be telling us?" and can build novel measurement frameworks where standard metrics may not yet exist.

• Seniority & Influence: You have experience driving large-scale initiatives. You can communicate complex data concepts to non-technical stakeholders and influence technical teams to prioritize data quality work based on your analytical findings.

• Technical Proficiency: High proficiency in SQL and Python is essential. You are comfortable building your own pipelines and utilizing modern data stack tools to unblock your analysis and prototype solutions.

• Strategic Thinking: You can balance the delivery of immediate analytical insights with the long-term vision of a robust, automated data health ecosystem.