Staff (Lead) Data Engineer

Staff (Lead) Data Engineer

Company Description

Shopify is the leading omni-channel commerce platform. Merchants use Shopify to design, set up, and manage their stores across multiple sales channels, including mobile, web, social media, marketplaces, brick-and-mortar locations, and pop-up shops. The platform also provides merchants with a powerful back-office and a single view of their business, from payments to shipping. The Shopify platform was engineered for reliability and scale, making enterprise-level technology available to businesses of all sizes.

Job Description

Our Data Engineering group builds and maintains the platform that delivers accessible data to power decision-making at Shopify for millions of merchants. We’re hiring high-impact developers across teams:

  • The Engine group organizes all merchant and Shopify data into our data lake in highly-optimized formats for fast query processing, and maintaining the security and quality of our datasets.

  • The Analytics group leverages the Engine primitives to build and deliver simple and useful products that power scalable transformation of data at Shopify in batch, streaming, or for machine learning. This group is focused on making it really simple for our users to answer three questions: What happened in the past? What is happening now? And, what will happen in the future?  

  • The Data Experiences group builds end-user experiences for experimentation, data discovery, and business intelligence reporting.

  • The Reliability group operates the data platform in a consistent and reliable manner. They build tools for other teams on Data Platform to leverage and encourage consistency as they champion reliability across the platform.

Qualifications

  • An experienced technical leader with a proven track record of delivering impactful results.

  • Technical engineering background in one or more areas in the next section.

  • Experience with technical mentoring, coaching, and improving the technical output of the people around you.

  • Exceptional communication skills and ability to translate technical concepts into easy to understand language for our stakeholders. 

  • Excitement for working with a remote team; you value collaborating on problems, asking questions, delivering feedback, and supporting others in their goals whether they are in your vicinity or entire cities apart.

A Staff (Lead) Data Engineer would typically have 6-10 years of experience in one or more of the following areas:

  • Experience with the internals of a distributed compute engine (Spark, Presto, DBT, or Flink/Beam)

  • Experience in query optimization, resource allocation and management, and data lake performance (Presto, SQL)

  • Experience with cloud infrastructure (Google Cloud, Kubernetes, Terraform)
    Experience with security products and methods (Apache Ranger, Apache Knox, OAuth, IAM, Kerberos)

  • Experience deploying and scaling ML solutions using open-source frameworks (MLFlow, TFX, H2O, etc.)

  • Experience building full-stack applications (Ruby/Rails, React, TypeScript)

  • Background and practical experience in statistics and/or computational mathematics (Bayesian and Frequentist approaches, NumPy, PyMC3, etc.)

  • Modern Big-Data storage technologies (Iceberg, Hudi, Delta)

Additional Information

As there are multiple positions, this posting will remain live until all positions have been filled. Successful candidates can expect to hear back from us within 2 weeks of application.

#LI-REMOTE

Our belief is that a strong commitment to diversity & inclusion enables us to truly make commerce better for everyone. We encourage applications from Indigenous peoples, racialized people, people with disabilities, people from gender and sexually diverse communities, and/or people with intersectional identities. Please take a look at our Sustainability Reports to learn more about Shopify’s commitments to our communities, and our planet.

At Shopify, we understand that experience comes in many forms. We’re dedicated to adding new perspectives to the team - so if your experience is this close to what we’re looking for, please consider applying.

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