Do you desire to work with large amounts of data? Are you interested in architecting data infrastructure while doing meaningful work? Have you always wanted your work to have a positive societal mission to help underserved communities?
As a Data Engineer at Possible, you will work on interesting, high impact and large scale data engineering projects. Key responsibilities including; build and deliver automated data pipelines, ingest and transform data from a plethora of internal and external data sources to a data lake in the cloud, data security, and integration with other systems at Possible. We are looking for a self-starter with the ability to deliver on time and is passionate about data to solve business problems.
This role requires a high level of collaboration as you work cross-functionally to answer key strategic questions and drive architecture decisions that will help Possible achieve the growth ahead. This role reports directly to the Head of Data Science and ML.
About Possible:
We are a fast-growing, fully distributed, fintech startup that believes financial health is something everyone deserves, not just the affluent. We're committed to empowering the underserved with tools to better their economic situation. We promise to be transparent, serve with kindness, be responsible, and hold ourselves accountable for creating positive change. Possible is backed by leading investors such as Union Square Ventures, Canvas Ventures, and FJ Labs.
Work hours:
Possible is fully distributed and has team members across the US and in Asia and Latin America. Our primary coordination hours are 9a to 3p Pacific Time.
Benefits (for US-based employees):
Joining an early-stage, venture-backed company does not mean you will sacrifice on benefits. We offer excellent medical, dental, and vision coverage and pay 85% of employee premiums and 50% of eligible dependent premiums. We also offer childcare and healthcare FSAs; life and disability (short- and long-term) insurance; an Employee Assistant Program; and a 401(k) plan.