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Engineering
Data Engineer
Where you can make an impact:
- Ideate, propose, and implement systems to create useful data for insights, predictions, and to help consumers manage their money more effectively.
- Educate Nerds about how to use and manage data in powerful ways.
- Increase trust in data, and make it easy to use.
- Participate in on-call rotation
Must have:
- Deep understanding of message-oriented / asynchronous, batch, and restful systems, and of databases, caches, and files. Especially on Linux and AWS.
- Proficient in Python, but we’ll work it out if you’re a master in Golang or Java.
- Experience with any of the following data products: Snowflake, Superset, Looker, Mode, Tableau, Amplitude, EMR, Redshift.
- Experience with scheduling tools, such as Airflow.
- Can speak SQL well, with an understanding of how query execution works under the covers.
- Solid communication skills in writing with offshore and influencing others.
- A bias for thoughtful action.
Great to have:
- Experience in data management practices, such as defining and validating quality, latency, metadata, and lineage goals.
- Experience with spark, flink, and python analytics tooling like pandas, numpy, scipy.
- Experience in FinTech or general financial services.