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    Analytics Engineer II - New York, United States - Public

    Public
    Public New York, United States

    3 weeks ago

    Default job background
    Full time
    Description

    About Public

    Public is an investing platform that makes building a multi-asset portfolio fast, frictionless, and secure. Members can trade stocks, options, bonds, crypto, ETFs, and alternative assets—all in one place. Alongside its robust suite of investing tools, Public offers Alpha, a layer of artificial intelligence that provides fundamental data and custom analysis to support informed investment decisions.

    Since 2019, Public has raised over $300 million. Investors include Accel, Tiger Global, Will Smith's Dreamers VC, The Chainsmokers' Mantis VC, and Shari Redstone's Advancit Capital, as well as renowned figures in business and culture, like Maria Sharapova, Tony Hawk, and NYU Stern professor Scott Galloway.

    About the role

    As a key member of Public's data analytics team, you will be responsible for the continuous development and optimization of our data infrastructure. Collaborating with stakeholders across the business, you'll leverage your SQL expertise to build ETL pipelines, create compelling data visualizations, and extract actionable insights from the data. Your contributions will directly influence pivotal business decisions across product, marketing, and finance domains, driving our organization's success through data-driven innovation and informed strategies.

    This is a hybrid role (4 days onsite) based in New York City and will report directly to Lead Analytics Engineer.

    What you'll do

    • Collaborate with product, finance, marketing, and brokerage ops to translate internal data into visually actionable data insights
    • Design and develop interactive Looker dashboards and reports to visualize key metrics and KPIs
    • Coordinate with frontend and backend engineers to align data requirements and design a robust data architecture that supports various business functions
    • Full stack analytics engineering development, building models to consume, transform, and expose data to stakeholders and production systems while ensuring data quality through strategic testing
    • Build centralized company metrics and data models for our BI layer using LookML
    • Perform analyses aimed at optimizing product and business metrics using a variety of methods including data visualization, backtesting, and data science methods
    • Participate in code reviews and provide feedback to other team members to ensure code quality and maintainability
    • Feed data-driven recommendations back to lifecycle marketing and backend databases through automated reverse ETL pipelines using HighTouch and Segment Reverse ETL
    • Maintain, optimize, and improve Public's data infrastructure across DBT, Looker, Snowflake, FiveTran, Airflow, and HighTouch

    Who you are

    • Proven experience (1-3 years) in data analytics, data engineering, or related roles, preferably in the finance or brokerage industry with experience using modern data pipelines and warehousing platforms (such as Snowflake, DBT, FiveTran, Airflow)
    • Strong SQL knowledge and ability to write efficient queries (preferably experience in Snowflake, Redshift, BigQuery)
    • Experience in administration of BI tools, building dashboards, and creating compelling data visualizations with dashboarding tools (ex. Looker, Tableau, PowerBI)
    • Excellent analytical and problem-solving skills with the ability to translate business requirements into technical solutions
    • Strong communication skills and can present data-driven narratives in both verbal and written form
    • Quick learner with ability to swiftly grasp the fundamental components of the business and the key drivers that influence company metrics
    • Investigative mindset, willing to think outside the box and contribute ideas across business functions

    Bonus Points

    • Interest in personal finance/ investing
    • Experience working in fast-paced, start-up environment in the FinTech and/or consumer brand space
    • Demonstrated interest or experience in applying machine learning to enhance business operations
    • Proficiency in data science languages such as Python and R
    • Expertise in marketing data attribution and performance measurement

    Public is an equal employment opportunity employer to all employees and applicants for employment and prohibits discrimination and harassment of any type. We celebrate people of all race, color, religion, age, sex, national origin, disability status, genetics, veteran status, sexual orientation, gender identity, or expression. The compensation range for this role is $115k-$135k, based on skills and experience.

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