Senior Solution Architect - Data Engineering

Who we are:

Founded in 1998 at Vancouver, lululemon is a performance and lifestyle product company that create transformational products and experiences that build meaningful connections, unlocking greater possibility and wellbeing for all. We are driven by our brand purpose to elevate human potential by making individuals feel their best which helps us design our products with high filter and high style. We use a unique product creation methodology called Science of Feel in all our products to offer convenient, comfortable, and long-lasting experience. We owe our success to our innovative products, commitment to our people, and the incredible connections we make in every community we're in.

Responsibilities:

You will be viewed as a strong technical leader with data architecture and engineering skills. Your background will include a proven track record of leading and scaling data engineering engagements and architecture, strong communication and collaborative skills, significant track record of working with data product teams and a strong vision for how data can inform business strategy.

• Designing Data & Analytics solutions leveraging AWS/Azure services
• Lead effort to develop technical standards to support and operate technologies within the current or future Microsoft Azure / AWS system platform
• Translate business and functional requirements into technical specifications including defining data collection and database schema requirements
• Work with cross-functional teams to help define master data management governance rules within a data mesh enterprise environment
• Recognize and adopt best practices in developing analytical insights including data integrity, analysis, test design and validation
• Proactively promotes data quality & data governance through recommended approaches and practices
• Provide strong technical leadership and mentor our team of Data Engineers

Qualifications:

• Hands-on knowledge and understanding of Snowflake, Data Modelling, Designing scalable solutions using AWS / Azure
• 9-12 years of software engineering experience Data Warehousing, Business Intelligence
• 7+ years of experience building data pipelines using Microsoft Azure tools and services (Azure Data Factory, Azure Blob, Azure Databricks,) or AWS services.
• Preferred experience in Oracle integration tools like Oracle Data Integrator & Oracle Golden Gate – Good to have
• 5+ years of experience with Python and PySpark
• Technical understanding of data model, data mapping, and data integration with a cross-functional mindset
• Demonstrated expertise with message brokers such as Kafka and containerization tooling such as Docker / Kubernetes – Good to have
• Demonstrated expertise with delivering end-to-end data products to business stakeholders (from source integration to reporting roll-out)
• Strong experience with data warehousing design principles and industry best practices including multi-dimensional modelling (star schemas, snowflakes, de-normalized models, handling slow-changing dimensions)
• Experience with the BI / DW lifecycle components including source data analysis, ETL, ODS, DataMarts, Reporting, Dashboards, and Analytics – Good to have
• Experience in working in Agile teams and working independently with Business stakeholders providing solutions and regular updates
• Team player, motivated to learn new technologies, and able to grasp concepts and technologies quickly with analytical and problem-solving skills
• Be able to build pilot solutions and proof-of-concepts with minimal direction