SeedsGroup is composed by 2 companies: TalentSeed and iTSeeds.

TalentSeed, company awarded with Excellence in HR for Startups by HR Magazine in 2017, is building Talent Management Solutions in areas like Assessment, Engagement, among other, available to all companies in the world

iTSeeds, a technological company, implementing technological solutions, outsourcing or Nearshore operations for clients all over the world

TalentSeed is currently recruiting for Toronto, Canada:

Full-Stack Engineer

Challenge

Our client is a data science company turning IOT sensor data into rich insights about people’s behavior and real-time context. While integrating this Engineering Team, you will be included in a fast-paced, high growth working environment, working with a Data Science team. You will be implementing and integrating microservices for data analysis with Data Scientists and Data Engineers in teams, working on both public and private API’s improving data accessability. You will create applications for data visualization and management and you will be involved in both the frontend and the backend processes.

Profile

• Minimum 3 years of experience working as a Full-Stack Engineer
• Desired skills and expertise
• Bachelor or Masters degree in  computer science or related field
• Solid background in Javascript (ES6), Python or Java (minimum of two)
• Experience with Angular, React, Vue or similar front-end frameworks
• Experience with RESTful services
• Professional experience with SQL and NoSQL databases
• Fluency in English is mandatory, Dutch is a plus
• Capacity to work independently
• Ability to learn and implement technologies quickly
• Creating high quality, reusable code and UIs.

Bonus skills

• Creation of interactive data visualizations using D3.js or simmilar tools

• Knowledge of functional programming

• Development of interfaces in web and mobile using CSS preprocessors

• Professional experience with Docker containers

• Experience with data visualization tools for data debugging 

• Professional experience with Kafka, Spark, or simmilar tools