The ad says“Deep experience in database design, warehouse data modeling, and developing distributed systems, including specific technologies utilized”
The ad says“Deep experience in database design, warehouse data modeling, and developing distributed systems, including specific technologies utilized”
The ad says“5+ years of software/data engineering experience with expert hands-on Python and SQL practice”
The ad says“5+ years of software/data engineering experience with expert hands-on Python and SQL practice”
The ad says“Deep experience in database design, warehouse data modeling, and developing distributed systems, including specific technologies utilized”
Values
The ad says“Predictive modeling and machine learning experience is a strong plus”
The ad says“Predictive modeling and machine learning experience is a strong plus”
This role is part of our Data Engineering team
Being Data Driven is a core value of Super.com and this team plays a huge part in this, enabling the organization to scale while maintaining petabytes of data
We are long time advocates and users of Snowflake, dbt, Kafka, and Amplitude
This isn’t a place where we are convincing the business the value of data or just using these tools for the first time
We have maturity in our technical practices, launch a new experiment almost every day, and we are looking for teammates to roll up their sleeves and do high quality data work
As a Senior Software Engineer, Data Platform, you will be a key member of a high-performing team of senior data professionals, reporting directly to an Engineering Manager
You will be expected to tackle the organization’s most difficult and critical technical challenges, providing robust, scalable, and reliable solutions that align with the company’s growth
This position is a specialized function within our SWAT (SoftWare Adaptability Team)
As a SWAT team member, your allocation will be driven by the organization’s highest short-term needs (6 to 26 weeks)
Success in this role requires a rapid contextual ramp-up to quickly diagnose complex problems, align solutions with diverse stakeholders, and design and implement high-quality, impactful data solutions
You must skillfully balance the need for rapid delivery with high-quality data outputs to maximize business value
Design efficient architectural recommendations, gain buy-in, and implement them in a reliable manner
Improve, oversee, and coach standards for code+infrastructure maintainability and performance through written documentation and peer review
Work closely with the analytics and business intelligence teams, as well as other stakeholders from finance, sales, marketing, and product, to identify the data needs of the business and produce processes that enable a better product and support growth decision-making
Champion and ensure data governance is a core component of engineering workflows
Help to evolve and scale our data platform, with an eye towards growth of our business and stability
Benefits
Competitive base salary
Yearly learning & development allowance
Generous equity options
Bi-annual performance & compensation reviews
RRSP & 401k employee contribution plan
Health, dental, & vision insurance on day one
Parental leave programs
Wellness reimbursement
Supplemental Life Insurance
Unlimited PTO (yes, really!)
Recharge days throughout the year
Office in Toronto
Work-from-home allowance
Permanent remote flexibility
Preferred experience
A track record of taking ownership in high-stakes situations, demonstrating urgency, and rapidly integrating new technologies to drive quantifiable business outcomes
Predictive modeling and machine learning experience is a strong plus
Evidence of designing and implementing logical, well-architected solutions for complex, large-scale data engineering challenges
5+ years of software/data engineering experience with expert hands-on Python and SQL practice
Deep experience in database design, warehouse data modeling, and developing distributed systems, including specific technologies utilized
Proven ability to clearly communicate intricate technical details and complex requirements to both technical peers and non-technical business stakeholders, leading to alignment and project success
