Senior Data Engineer, Embedded

Stack

Responsibilities

• ▹Work with business partners to understand business and product objectives and identify the data needed to support them
• ▹Design, build, implement and document data models
• ▹Write data transformations using dbt or Spark
• ▹Ship data pipelines, including real-time streaming and batch processing
• ▹Optimize transformation pipelines to increase freshness or reduce computational time and cost
• ▹Work with engineers to understand and influence how data is produced
• ▹Collaborate with other data engineers on tooling to automate consuming, validating and updating raw and modeled data
• ▹Follow the architecture and standards of the Data Engineer craft at Shopify
• ▹Collaborate with sister disciplines (Engineering, Data Science) to establish and promote data engineering best practices
• ▹Partner with product, engineering and business leaders to influence product and program decisions with data
• ▹Build production-quality dashboards and scalable data products, and perform product analysis from time to time

Requirements

• ▹Commercial experience in Data Engineering and/or Analytics Engineering, building scalable data warehouses
• ▹Dimensional modeling (Star Schema, Kimball, Inmon)
• ▹Advanced SQL skills (window functions, defining UDFs)
• ▹Exposure to data engineering tooling: ingestion, testing transformations, lineage, orchestration, publishing data, metric layers
• ▹Hands-on experience implementing real-time and batch data pipelines with tight SLOs and complex transformation requirements
• ▹Fantastic collaboration and communication skills, demonstrated by successful large-scale projects spanning multiple teams
• ▹Technical thought leader, comfortable navigating ambiguity and mentoring team members at various levels
• ▹Aptitude for product analysis, dashboarding and reporting

Soft skills

About the company

Shopify has been operating since 2006, has around 10,000 employees and helps merchants in 175 countries start and grow their businesses. Data is central to its mission: it organizes and interprets petabytes of data for merchants and internal teams.