Senior Data Engineer
Remote - United States
Full Time Senior-level / Expert USD 133K - 202K
THE COMPANY:
Juul Labs's mission is to transition the world’s billion adult smokers away from combustible cigarettes, eliminate their use, and combat underage usage of our products. We have the opportunity to address one of the world’s most intractable challenges through a commitment to exceptional quality, research, design, and innovation. Backed by leading technology investors, we are committed to the same excellence when it comes to hiring great talent.
We are a diverse team that is united by this common purpose and we are hiring the world’s best engineers, scientists, designers, product managers, operations experts, and customer service and business professionals. If the opportunity to build your career is compelling, read on for more details.
ROLE AND RESPONSIBILITIES:
Data at Juul means working with varied, large, data sets – where we apply analytical methods to help inform and drive business and product decisions. We are looking for an output-focused problem solver with a strong conceptual mindset and superb communication skills.
The team sees itself as analytical generalists – we choose the right technique for each problem, pride ourselves on building beautiful systems and dashboards while moving fast, and are ultimately driven by the value and insight data science can generate for the business and our customers. Our work directly impacts and shapes key executive decisions. This role offers tremendous upwards exposure towards senior business leaders and the chance to truly impact the decision making in a startup.
KEY RESPONSIBILITIES:
- Design robust, reusable and scalable data solutions and data pipeline frameworks to automate the ingestion, processing and delivery of both structured and unstructured data using python
- Be in active development of large-scale data engineering projects
- Create data pipelines in airflow, DBT and the general suite of Google Cloud Platform
- Build, manage, and support data models. Ensure data quality with data tests in Monte Carlo and Datafold
- Modeling the dynamics of the fast moving and competitive market that we operate in and understanding our impact on it
- Bringing visibility into our complex sales, logistics and supply chain operations through dashboards and standardized metrics
- Explaining and predicting online and offline consumer choices and consumption patterns
- Building demand forecasting models and understanding their behavior
- Creating clean analytical data models and tools to help empower business and operational teams
- Work in a scrum agile environment using Trello
- Partner with Data Scientists, Data Engineers and Business Analysts to build configurable, scalable, and robust data processing infrastructure
- Work closely with our sales, operations, research, and finance teams on data storage, retrieval, and analysis
- Develop new systems and tools to enable stakeholders to consume and understand data more intuitively
- Create and establish design standards and assurance processes to ensure compatibility and operability of data connections, flows and storage requirements
- Keep Juul on the cutting edge of data technology
- Our Data Stack:
- Google Cloud Platform - GCP (BigQuery, Storage, Pub/Sub, Cloud Run, Vertex AI, Cloud Build)
- DBT
- Airflow, Fivetran
- IO
- Hex, Tableau, Mode, Jupyter Notebooks
PERSONAL AND PROFESSIONAL QUALIFICATIONS:
- 4+ years of data engineering or software engineering experience with a focus on data
- Significant experience in independently driving engineering solutions
- Advanced knowledge in developing using Python for data processing for large-scale datasets and workflows
- Skilled using python libraries and packages (Pandas, PyArrow) in conjunction with the Google Cloud Platform (BigQuery, Storage, Pub/Sub)
- Comfortable working on AI pipelines (Vertex AI, Claude)
- Knowledge of bash/shell and orchestration tools (e.g. Airflow), is preferred
- Experience with version control (Git) and containers (Docker)
- Skilled in analytical SQL in support of data modeling/ transformations and manipulating multiple data formats
- Foundational expertise of deploying and maintaining machine learning pipelines is a plus
EDUCATION & EXPERIENCE:
Preferred masters degree in Computer Science, Engineering, Math, or equivalent experience
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
- Cell phone subsidy, commuter benefits and discounts on JUUL products
- Excellent medical, dental and vision, disability, and life insurance, plus family support, wellness, legal, and employee assistance program benefits
- 401(k) plan with company matching
- Plus biannual discretionary performance bonuses
SALARY RANGES:
Salary varies by role, level and location, and is dependent on the cost of labor in a given
geographic region among other factors. These ranges may be modified at any time.
LOCATIONS:
Tier 1 Locations: Greater New York City, and San Francisco Bay Area
Tier 2 Locations: Greater Boston, Washington DC Metropolitan Area, Seattle/Tacoma,
Greater Sacramento, Southern California (Los Angeles/OC/San Diego, Riverside and Imperial counties)
Tier 3 Locations: Rest of New England, NY Capital District, Rest of New Jersey, Greater
Philadelphia, Pittsburgh, Delaware, Rest of Maryland, Rest of Virginia, North Carolina,
Atlanta, Miami-Fort Lauderdale-WPB, Chicagoland, Dallas, Houston, Austin,
Minneapolis/St. Paul, Colorado, Phoenix, Reno, Las Vegas, Reno, Carson City NV., Portland Ore./Vancouver
Wash., Rest of California, Hawaii
Tier 4 Locations: Rest of US including Alaska and Puerto Rico
Tags: Agile Airflow BigQuery Claude Computer Science Data pipelines Data quality dbt Docker Engineering Finance FiveTran GCP Git Google Cloud Jupyter Machine Learning Mathematics Monte Carlo Pandas Pipelines Python Research Scrum SQL Tableau Unstructured data Vertex AI
Perks/benefits: Career development Competitive pay Equity / stock options Health care Insurance Startup environment
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