Analytics Engineer L5

$100,000 - $700,000/Yr

Netflix - Los Angeles, CA

Full-time

Los Angeles, CA

Broadcasting and Content Providers

About the position

The position involves leading end-to-end analytics and data needs for the N-Tech Engineering & Reliability organization at Netflix. The role focuses on improving employee productivity through data-driven insights and solutions, directly impacting strategic decisions and operational efficiency. The successful candidate will collaborate with various teams to analyze data, develop reports and dashboards, and communicate findings to stakeholders, ultimately enhancing the overall employee experience at Netflix.

Responsibilities

• Be a strategic partner for N-Tech teams/leads: identify critical analytical problems and apply an entrepreneurial mindset to find innovative solutions with data.
• Lead end-to-end development of reports, dashboards, and tools used by your direct stakeholders and diverse teams across the company.
• Partner with UX designers and engineers to ensure we have the data to learn and measure impact.
• Conduct statistical analyses and modeling, exploratory analysis, and metric development to uncover data insights and inform key decisions.
• Proactively perform data exploration and analytical deep dives to discover insights for future opportunities.
• Be a bridge between the business and tech, scaling access to insights that can empower better decision-making.
• Deliver data insights and drive for adoption through tools (e.g., dashboards, self-serve reporting), memos, and presentations.
• Drive the direction and execution of your work, which can range from developing scrappy analytic tools to designing scalable analytic systems.
• Develop scalable data pipelines to collect, clean, and analyze data from various sources; prototype and productionize metrics and models.
• Collaborate with cross-functional engineering teams to solve similar business problems and drive consistency in creating and comparing metrics.
• Balance handling engineering efforts, analytical deep dives, and building analytic products.
• Facilitate data ownership and accountability by closely partnering with data engineering, product, and engineering partners to improve data robustness.

Requirements

• A background in statistics, math, data science, or a similar quantitative field, with strong statistical skills and intuition.
• 5+ years of experience in leveraging technical skills in manipulating large data sets with complex SQL and Python (or similar languages), big data technologies (e.g., Hadoop, Spark), and visualization tools (e.g., Tableau).
• Excellent at translating raw data sources (i.e., APIs) into analytics-ready data sets that serve business needs.
• Experienced at extracting data from APIs as part of regular ETL workflows, with an eye toward data quality.
• Expertise in SQL programming skills (e.g., Python, Scala) and proficiency with designing ETL flows.
• High proficiency in statistical programming, Python preferred.
• Experienced with developing data tools, memos, and presentations to deliver data and insights to stakeholders.
• Experience in solving problems in technical, product, or other engineering areas is a plus.
• Enthusiasm for acquiring knowledge in unexplored areas, coupled with the adaptability to overcome challenges as they arise.
• Highly effective in engaging with diverse stakeholders and adept at cultivating strong partnerships.
• Strategic-minded, impact-driven, and capable of incorporating larger business context into data questions and product development.
• Comfortable with ambiguity; able to take ownership, and thrive with minimal oversight and process.

Nice-to-haves

• Experience in solving problems in technical, product, or other engineering areas is a plus.

Benefits

• Annual salary compensation structure with flexibility in choosing between salary and stock options.
• Equal opportunity employer with a commitment to diversity and inclusion.