Data Engineering Manager (Revenue)
Company Description
Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. Since 2006, we’ve grown to over 10,000 employees and generated over $500 billion in sales for millions of merchants in 175 countries. Every 28 seconds, an entrepreneur on Shopify makes their first sale.
This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.
About you
Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.
Before you apply, consider if you can:
- Care deeply about what you do and about making commerce better for everyone
- Excel by seeking professional and personal hypergrowth
- Keep up with an unrelenting pace (the week, not the quarter)
- Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
- Bring critical thought and opinion — and embrace differences and disagreement to get shit done and move forward
- Work digital-first for your daily work
Job Description
Data is a crucial part of Shopify’s mission to make commerce better for everyone. We organize and interpret petabytes of data to provide solutions for our merchants and stakeholders across the organization.
Data is the voice of all our customers – merchants, buyers, developers – and hearing this voice clearly is critical to us making commerce better for them. As a Data Engineering Manager working with the Revenue organization, your primary responsibilities will be to build first class data assets that drive a 4500-person organization that is responsible for bringing Shopify to the world. Leading a team of Data Engineers, you’ll unlock a large number of analyses on varied topics not only now but in the future and will also provide a complete view of Shopify’s business.
Given the launch of Shopify Commerce Components, you’ll be working with one of the fastest growing parts of Shopify.
Example day to day responsibilities include:
- Leading Data Engineering team members, identifying and developing their technical acumen, collaboration skills, and other areas of growth
- Developing a roadmap of deliverables in collaboration with key stakeholders
- Partnering as a member of the Revenue Data Science & Engineering team to influence and accelerate this crucial space at Shopify
- Overseeing technical development of key commercial activity pipelines (eg. Sales funnels, Marketing touchpoints, etc.)
- Creating and implementing architecture and standards used by all Shopify Data Engineering teams
- Collaborate with sister disciplines (Engineering, Data Science, Machine Learning) to establish best practices
- Working with data scientists and business partners in the Revenue org to understand requirements
- Working with developers to understand how data is produced, and advise on appropriate technical solutions
- Overseeing ICs that design, build (using dbt or Spark) , profile, and document our datasets and the jobs that build them
- Debating whether leading or trailing commas are better
Qualifications
- Commercial experience in Data Engineering, and/or Analytics Engineering, building scalable data warehouses
- Proven leadership in managing data engineers to optimize data infrastructure and drive organizational performance
- Building teams, maintaining a healthy, collaborative team culture
- Exposure to Data Engineering tooling: ingesting, testing transformations, lineage, orchestration, publishing data, metric layers
- Fantastic collaboration and communication skills, demonstrated by successful large-scale projects spanning multiple teams
- Technical thought leader, comfortable navigating ambiguity and mentoring junior team members
Additional Information
All your information will be kept confidential according to EEO guidelines.