Analytics Engineer: Build Insightful Dashboards & Pipelines

MaziCTools; United States; Remote; USD 48,000 - 55,000; Full time

Job summary

Netflix is seeking an Analytics Engineer in California to join the Buyer Insights & Analytics team. You will develop scalable data pipelines and collaborate with quantitative scientists to drive business decisions.

The role emphasizes building self-serve dashboards and contributing to data models and visualizations using SQL, R, Python, and Looker. You will partner with analysts and engineers on high-impact projects.

Qualifications

• Postgraduate education in statistics, computer science, science or related field or substantial industry experience.
• Strong programming and data wrangling skills using SQL, R and Python, with version control experience.
• Experience building multi-step ETL jobs and data pipelines with scheduling systems.
• Experience creating layered warehouse data models.
• Solid data visualization skills with dashboards and storytelling; familiarity with Looker is a plus.
• Ability to thrive with minimal supervision and drive projects forward.
• Experience working with external APIs for data ingestion is a plus.
• Interest in review or social data is a plus.

Responsibilities

• Build and maintain adaptable data pipelines to manage review and social data for analytics use cases.
• Identify key questions and translate them into analytic approaches.
• Collaborate with Customer Insights Scientists to define problems and craft solutions.
• Create intuitive dashboards with business-focused visualizations.
• Own dashboards and tools for self-serve analytics.
• Partner with engineers, designers and researchers to guide analyses.
• Develop data-driven stories to answer hard entertainment questions.

Skills

SQL

R

Python

Git

Education

Bachelor Degree

Tools

Looker

R Shiny

Tableau

Job description

Netflix is seeking an Analytics Engineer in California to join the Buyer Insights & Analytics team. You will develop scalable data pipelines and collaborate with quantitative scientists to drive business decisions.

The role emphasizes building self-serve dashboards and contributing to data models and visualizations using SQL, R, Python, and Looker. You will partner with analysts and engineers on high-impact projects.