THE COMPANY:

JUUL's mission is to improve the lives of the world’s one billion adult smokers by driving innovation to eliminate cigarettes. JUUL is the number one US-based vapor product. Headquartered in San Francisco and backed by leading technology investors including Tiger Global, Fidelity Investments and Tao Invest LLC, JUUL Labs is disrupting one of the world’s largest and oldest industries.

We’re an exceptional team with backgrounds in technology, healthcare, CPG and biotech, and we’re growing rapidly to deliver on our mission. We’re actively looking to hire the world’s best scientists, engineers, designers, product managers, supply chain experts, customer service and business professionals.

ROLE AND RESPONSIBILITIES:

Producing and distributing a physical product at a global scale, while at the same time setting standards in innovation is a difficult task. To achieve this goal at JUUL, we employ a data-driven approach using our cloud-based data platform as the basis.

As a Senior Analytics Engineer within the Data Team, you will be part of the group responsible for our data platform. Specifically, your responsibilities will include:

  • Work with data scientists and analysts to determine data model requirements
  • Ingest internal and external data sources and transform them into clean and abstracted data models
  • Build semantic layers in BI tools (e.g. Tableau and Looker) to help analysts build dashboards on top of the data
  • Work with data scientists to productionize data science workflows

While you will be part of the Analytics Engineering group and learn from highly-skilled and like-minded people, you will also be assigned and closely work with a group of data scientists and data analysts who focus on solving problems of a specific business area (e.g. Product, E-Commerce, Supply Chain). This enables you to see and be part of the end-to-end analytics and data science workflows.

PERSONAL AND PROFESSIONAL QUALIFICATIONS:

  • 6+ years experience in an analytics/data engineering or systems analyst role
  • Advanced SQL and Python skills allowing you to write ETL jobs
  • Experience managing complex interdependent pipelines
  • Proficient in data visualization, dashboarding and analytical report building (Tableau, Looker, Mode, or similar)
  • Understand fundamental concepts of good data modeling such as entities, relationships, normalization and unit testing
  • Proven critical thinking and analytical problem-solving skills
  • Ownership mentality - you get things done and deliver high quality output without having to be told what to do
  • Strong track record of delivering outcomes in high-pressure, fast-paced environments
  • Experience communicating and working with business analysts, data scientists, product managers and business stakeholders alike

Bonus Skills:

  • Familiarity with modern cloud data infrastructure (GCP, AWS)
  • Experience in a fast-growing start-up or leading enterprise tech company (e.g. Amazon, Apple, Uber or similar)
  • Ability to navigate and live in a modern data engineering environment

EDUCATION:

  • Bachelor’s degree or higher from a top university in a quantitative field

JUUL LABS PERKS & BENEFITS:

  • A place to grow your career. We’ll help you set big goals - and exceed them
  • People. Work with talented, committed and supportive teammates
  • Equity and performance bonuses. Every employee is a stakeholder in our success
  • Boundless snacks and drinks
  • Cell phone subsidy, commuter benefits and discounts on JUUL products
  • Excellent medical, dental and vision benefits
  • Location. Work in New York or San Francisco, two of the world’s greatest cities
Vapor, JUUL, Work Culture, Fast Paced, Start-up, Growth, Vape, Technology, Software, Hardware, Consumer Electronics, Manufacturing, Design, Product, Disruptive, Revolutionary, Cutting Edge, App, Android, iOS, eCommerce, B2C, San Francisco, Bay Area, IoT, San Jose, Los Angeles, New York, NY, NYC, New York City, Data, Data Science, Data Engineering, Analytics Engineering, Data Analysis, Data Modeling, Python, DBT, Pandas, BigQuery, Snowflake, Fivetran, Looker, Mode, Tableau

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