Prior Listings
Senior Analytics Engineer
Senior Analytics Engineer
This job is no longer open
The Petal mission
Petal’s mission is to bring financial opportunity and innovation to everyone.
We're pioneering a new approach to credit, by analyzing an applicant’s banking history, in addition to credit history, to determine their creditworthiness. We call this technology a Cash Score — and it takes into account income, spending, and savings. It’s currently helping thousands of people qualify for credit at better rates, even if they’ve never had it before.
We bring the same ingenuity to our credit card products. Our simple and intuitive app gives members access to credit score tracking, budgeting tools, subscription management, and automated payment options—everything they need to make financial progress.
Now more than ever, Americans need help improving their credit safely, responsibly, and affordably. If this sounds like something you’d like to be a part of, apply now, and let’s change this trillion-dollar industry together.
At Petal, we're looking for people with kindness, positivity, and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and potential will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. At Petal, we welcome diverse perspectives from people who think rigorously and aren't afraid to challenge assumptions.
The Senior Analytics Engineer Role
As our first Senior Analytics Engineer, you will be in charge of shaping this function by interacting with every team at Petal. You will sit at the intersection of our business teams, data engineering and data analytics, and will be responsible for building, maintaining and improving our data environments (introduction of new ETL tools, warehouse, data model in dbt, BI tool). This is a key role that will help mature Petal’s data function across the organization, and overall help Petal grow faster and scale efficiently.
Key Responsibilities:
- Build and maintain complex data models in dbt, and their corresponding data dictionary
- Ensure that these data assets are tested, documented and up to date
- Define quality standards for our data assets, and build corresponding alerts
- Optimize transformation workflows to increase query performance and speed of access to insights
- Lead the ETL process to add new data sources into the warehouse to answer key operational questions
- Closely collaborate with different teams in order to understand business requirements for the different data models
- Build and maintain analytics workflow best practices for a growing team of analysts
- Support data security and privacy efforts with our infrastructure team
- Work towards creating a metrics-driven and data-informed culture at Petal
Characteristics of an ideal candidate:
- 4+ years of experience in a data team, as an analytics engineer, data analyst or data engineer
- Experience working in a fast growing startup environment
- Willingness to get your hands dirty with messy data to build data models
- Mastery of SQL and Python
- Experience with dbt (and Airflow is an extra-plus)
- Experience building reports and dashboards in a BI tool (preferably Looker)
- Experience working with data extraction and loading tools (ie. Fivetran or Stitch)
- Knowledge of Data Engineering tools (incl. AWS)
- Strong attention to detail and high standards for the quality of deliverables
- Ability to work collaboratively on cross-functional projects between several different teams
- Passionate and a self-starter who drives high impact projects forward with minimal guidance
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This job is no longer open