Humu

Senior Data Engineer

Seattle, WA San Francisco, CA
USD 160k - 220k
Java Python GCP AWS Azure
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Description

 

Who we are

We're a team on a mission to make work better for everyone, everywhere. We empower people to thrive at work, without creating more work for them. 

Humu is an HR technology platform that makes it easy for organizations and their people to improve, every single week. Science shows that the fastest path to improvement is via personalized coaching in the flow of work. That’s exactly what Humu does. Humu nudges managers and their teams to build better habits that will lead to their success. Unlike most tools, Humu combines Nobel-prize winning science and technology to pinpoint which behaviors and people skills leaders, managers, and employees need to be effective. Humu helps customers drive outcomes like improving managers, increasing agility, building more inclusive cultures and boosting team performance.

Humu was founded in 2017; in 2021 we raised a $60M Series C round and we’re excited to grow our ~100-person company. We started with an office in Mountain View, CA; we still have that office, but we’ve since hired many employees  across the US and plan to continue supporting a remote-first culture.

We’re looking for passionate collaborators who are excited about building a product that empowers people to improve themselves, and the teams around them.

What you’ll get to work on

Humu’s Nudge Engine® deploys thousands of customized nudges—small, personal steps—throughout organizations to empower every employee, manager, team, and leader as a change agent. Over time, our nudges grow increasingly aware of the timing, messaging, and motivational techniques that inspire individual employees towards action.

As a member of Humu’s Data Engineering team, you will be responsible for building and maintaining systems focused on expanding and optimizing data pipelines to compute insights and analyses at scale. Some of the team’s major ownership areas include:

  • A data pipeline tool for helping transform ingested HR data into a consistent and clean format.
  • The automated processes for deciding which nudges to send to users, scheduling them for delivery, and delivering them through a multitude of formats (email, text messages, etc).
  • The logic and systems to make data available to a variety of cross functional teams at Humu.

Where you fit in

We are committed to change the working world for the better by bringing greater meaning and happiness into everyone's working lives, everywhere. We are passionate about our mission, and excited to grow our school of fish with people who want to do the same - and people who will bring in their different perspectives to help us continue to shape our team and product. If this is you, we encourage you swim into our candidate pool!

The details

Role and responsibilities:

  • As a member of our Product Team, you will ensure optimal data delivery architecture is consistent throughout ongoing projects.
  • Create and optimize our data pipeline architecture
  • Build data access platform for our data science and tech teams
  • Manage and optimize customer ingestions for the Humu product
  • Add and improve logging and monitoring
  • Willingness to occasionally implement UI for internal data tools.

Qualifications:

  • 5+ years of experience managing data pipelines
  • Driven engineer that is motivated to build a great product and great codebase in a fast-paced environment
  • Strong communication skills with a growth and learning mindset
  • Understanding of object-oriented languages (Java, Python, etc.)
  • Familiarity with cloud based platforms - GCP (Preferred), AWS, Azure
  • Experience with large-scale databases (preference towards non-relational unstructured databases).
  • Usage or understanding of complex data pipelines.
  • Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.

 

Salary range: $160,000 - $220,000

Only open to candidates in Seattle, WA or SF Bay Area, CA

Humu
Humu
Artificial Intelligence Human Resources Machine Learning

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