Tags: jd EarninCo DataAnalystDataScientist DataEngineer
ABOUT EARNIN:
Earnin is a community-supported financial platform with a suite of tools that let people take control of their financial future. One of the greatest – and least discussed – inequities in the American financial system today is the practice of employers paying workers bi-weekly. We’re building a better system with our core tool, Cash Out, which allows people to access the money they’ve already earned ‒ with no fees or interest. People simply pay what they think is fair.
Other tools include: Balance Shield, which helps prevent overdrafts, a financial calendar that helps people budget and schedule payments, and Tip Yourself ‒ a revolutionary free feature that makes putting money aside simple, social, and fun!
Funding: Series C, current funding partners include Andreessen Horowitz, DST, Matrix Partners, Ribbit Capital, Felicis Ventures, and March Capital.
Join us and help build a new financial system focused on fairness and people’s needs.
You can help make a difference!
ABOUT THE TEAM:
We are a data driven mobile financial tech company. The Data Engineering team builds the tools and data products that power data science, analytics, and product development at Earnin. We are looking for a product-minded, self-driven Data Engineer to help us advance our mission of enabling people to gain access to their paycheck on demand.
WHAT SETS US APART:
High impact roles at a relatively small company that’s aggressively growing our user base. We are a collaborative team and genuinely enjoy working with each other. We believe in empowering our people to be successful. We’re building a product that inspires fairness across the financial world.
WHAT YOU’LL DO:
Translate complex, open-ended problems into elegant design and build high quality, maintainable data products and tools. Design and build massively scalable, production-grade data services and pipelines that power machine learning model development and actionable analytics. Build robust and reliable data products that enable automated reporting, experimentation, A/B testing, anomaly detection, and root cause analysis. Work with data scientists and analysts to productionalize model deployments and pipelines. Champion data quality and governance throughout Earnin by maintaining and extending a clean data ecosystem for the company. Actively engage and drive design reviews and code reviews. Work cross functionally with other teams (data science, design, product, marketing, and analytics) in high visibility roles. Communicate the tradeoffs of technical decisions to multiple stakeholders, including non-technical audiences. WHAT WE’RE LOOKING FOR:
BS or MS degree in Computer Science, Engineering, or a related technical field. Excellent written and verbal communication skills, including the ability to identify and communicate data driven insight. Curiosity and a drive to learn. Willingness to be assertive and drive solutions independently. 4+ years of development experience in a fast-paced environment. 4+ years of experience working with analytical data systems and building production applications. Advanced knowledge of analytical SQL and data modeling. Strong Python programming skills. Experience building, deploying, maintaining, and tuning Spark-based applications. Taking pride in your code quality and helping others elevate their own code quality. Substantial experience developing production ETL processes. Substantial experience with testing, data validation, and data quality assurance. Hands-on experience working with a varied set of data storage technologies (e.g. Mysql, Postgres, DynamoDB?, S3, etc.). You know where and when to use each. Experience with physical data modeling on cloud storage: file formats, compression, partitioning strategies, etc. Experience with cloud data platforms like Snowflake or Databricks and/or cloud data warehouses like Redshift. Experience with BI tools like Looker, Tableau, and Periscope. NICE TO HAVES:
Experience building and deploying machine learning models is a big plus. Experience working with streaming infrastructure like AWS Kinesis and/or Kafka is a big plus. Experience with data modeling in Redshift is a big plus. Experience using query engines like Athena, Presto, and Impala is a big plus. Experience using Terraform is a big plus. Experience deploying microservices and jobs on Kubernetes infrastructure is a big plus. Experience working with alerting and monitoring tools like DataDog? and PagerDuty?. Substantial experience working at a startup. Experience building and deploying AWS Lambda applications. Experience with workflow orchestration tools like Airflow.