Analytics Engineer
New York, NY

Job Description

About Us

Venmo was founded on the principles of breaking down the intimidating barriers around financial transactions to make them intuitive, friendly, and even fun. And it worked: people love sending money with Venmo, and we're growing by leaps and bounds!

But we're only just getting started. We want to take that magic of sending money with Venmo and cascade it into every place where people use money. That means connecting people to their money in the most intuitive and fun way possible, then connecting people with each other. Users already love Venmo, but we know there are lots of things we haven't thought of to make the experience of using Venmo even more delightful and valuable. All that's going to take a lot of figuring out. Let's figure it out together!

Data Analytics at Venmo

We're a scrappy, diverse data team working hard to keep up with a fast paced company. We enable the Product, Marketing, and Business teams to make the best data-driven decisions each step of the way from ideation to execution. Our data stack includes Luigi, Kafka, Redshift, DBT, Looker, and Jupyter notebooks and follows the modern ELT philosophy. Our team sits together working out of our NYC office in the West Village where we are frequently brainstorming novel ideas and hack on new tools.

What You'll Do

While our team regularly interfaces with external stakeholders throughout the company, you would work more closely within our team being the domain expert of modern columnar data warehouses, leveling up the team's SQL standards, batch processing protocols, and data modeling skills through pairing sessions and thoughtful code review. Set a new level of expectations for data quality and collaborate with colleagues to ensure that contributions to the data warehouse are up to snuff.

You'll have the opportunity to re-architect and manage the analytics layer of our team's data environment to make data standardized and easily accessible to both our team and BI tools by writing production-quality transformations in dbt.

You would be maintaining and fine tuning our data warehouse and refactoring slow inefficient queries. You would also be working closely with Product and Engineering to ensure upstream additions and changes to production are modeled intuitively in our data warehouse.

What We're Looking For

* 3+ years of relevant experience in a data role
* Worked with business stakeholders to understand problems, DBAs to understand data sources, and have played the pivotal role of architecting data models to meet consumer needs
* Demonstrable experience in a similar role, within a fast-paced, high growth technology company
* 3+ years working with a data warehouse (e.g. Redshift, Snowflake)
* 2+ years experience with self-service BI tools (e.g. Tableau, Looker)
* SQL wizard experienced in data modeling, query performance and optimization
* Exposure to dbt, Luigi, Airflow or other DAG frameworks
* Proficient in Python
* Experience with ELT batch processing 100M+ rows daily
* Proficient with Git and CI/CD best practices
* A solid math and statistics background

Do you enjoy solving data problems with solutions that scales?

Does a good README.md make you feel warm and fuzzy inside?

Does "dry" describe your work better than stale bread?

Does the thought of a denormalized data feel a little wrong even if it helps with performance?

Do you enjoy working closely with a fun team of data enthusiasts?

If you answered yes to all these questions then we'd love to hear from you!

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.