Our partner is one of the largest retail e-commerce companies in North America. The team supports software and hardware used in stores by more than 40,000 employees, powering everything from point-of-sale systems and handheld devices for tailoring, to stylist tools, curbside pickup, and innovative digital experiences for customers.

In scope of a large-scale cloud transformation, we are rebuilding the ecosystem to improve scalability, performance, cost, and security. Some legacy services are being replaced with modern solutions built on Kubernetes, AWS, and Kafka.

Overall, if you like to communicate with customers and explore how things work at complex infrastructure, this might be the right project for you

A Data Analyst interprets data and turns it into actionable insights to improve business decisions. The analyst gathers information from various sources, applies statistical analysis and data modeling, and reports findings through dashboards and visualizations to business stakeholders.

• Design and develop data pipelines and ETL processes using Apache Airflow and Google Cloud Dataflow

• Extract and analyze large datasets from relational databases (BigQuery, Redshift, Oracle, Teradata) using SQL

• Perform data analysis using Python and SQL with advanced statistical methods

• Create data visualizations using Tableau, Power BI, or R-Shiny

• Conduct hypothesis testing and A/B testing for business insights

• Use Git for version control and collaborative development

• Optimize database queries and create views across multiple tables

• Report analytical findings to business stakeholders

• Bachelor's degree in quantitative field (Statistics, Computer Science, Data Science, or related)

• 4+ years of experience in data analysis

• Proficiency in Python and SQL

• Experience with Apache Airflow for workflow orchestration

• Experience with Google Cloud Dataflow and ETL processes

• Experience with relational databases (BigQuery, Redshift, Oracle, or Teradata)

• Proficiency with data visualization tools (Tableau, Power BI, or R-Shiny)

• Experience with Git version control

• Knowledge of statistical analysis and hypothesis testing