Engineering Team Lead, Alteryx Promote

Alteryx is looking for a Team Lead for the Promote product, which is an end-to-end data science platform for developing, deploying and managing predictive models and real-time decision APIs. A successful team lead will be a player-coach - someone that can help keep the team moving forward, but also step in and get your hands dirty when necessary. You will be managing a small group of talented, motivated engineers delivering a cutting-edge software product. The stack is a set of microservices built on Node, React, Docker, and SQL, while our customers are data scientists and business analysts using Alteryx Designer, R and Python.

Responsibilities:
* Manage, mentor, and develop a team of 3-5 engineers.
* Build and grow a collaborative high functioning team.
* Define the vision for your team. You should understand and be able to effectively communicate the intimate details of how to build a given feature, and be able to break down into (estimable) tasks.
* Work with the team to ensure solid engineering practices are followed and they are successful with the agile framework.
* Run/implement and attend scrum ceremonies (standup, refinement, iteration planning, etc...). You should know what everyone is working on, removing blockages, and how it impacts other teams.
* Perform code reviews for the engineers on your team to ensure delivery of clean, performant software.
* Work with the product management team and your team members to break product requirements into actionable work.
* Work with engineers, other team leads, and architects to design a quality product.
* You will be expected to be a servant leader and demonstrates the values of Alteryx and the product development organization

Desired Skills:
* 3+ years in Software Development, preferably full-stack
* Strong communication skills and technical background
* Passion for delivering quality software
* Deep knowledge of JavaScript (NodeJS and React+Redux)
* Familiarity with Docker and microservices is a plus
* Nice to have - experience with statistical and predictive modeling