DCM INFOTECH LIMITED
Full Stack Lead
Client - Lululemon
Fulltime
Location - Vancouver, BC/
Seattle, WA ( need to travel once in 3-4 months) Salary - CAD 160 k - 175K (USD $150k)
Mandatory Skills : Airflow and SQL
About the Role This is a role that blends
technical leadership ,
product thinking , and
data-driven innovation . You'll lead a team of engineers in building full stack applications that integrate with , leverage
machine learning models , and deliver real-time insights to planners, merchandisers, and supply chain teams. Key Responsibilities
Lead full stack development
using technologies like Angular, React, Node.js, GraphQL, and cloud-native services (AWS/GCP). Design and build integrations
between Anaplan and internal systems to support planning, forecasting, and scenario modeling. Collaborate with data scientists
to operationalize ML models for demand forecasting, inventory optimization, and supply chain analytics. Develop intuitive tools
for planners and business users to interact with forecasts, adjust plans, and simulate outcomes. Establish and maintain CI/CD pipelines
using Gitlab to automate testing, deployment, and monitoring. Mentor engineers
and promote best practices in architecture, testing, and DevOps. Champion strong engineering practices , including:
Test-driven development (TDD) Code reviews and pair programming Scalable architecture and modular design Observability, logging, and performance monitoring
Drive agile product development , working closely with Product, UX, and Planning teams to deliver high-impact features. Qualifications
9+ years of experience in software engineering,
with 2+ years in technical leadership role. Strong full stack development skills with modern frameworks (React, Next.js, Node.js). Familiarity with
AI/ML concepts , especially in time series forecasting, demand sensing, or optimization. Experience deploying ML models into production environments (e.g., using SageMaker, Vertex AI, or custom APIs). Proven experience implementing and managing
CI/CD pipelines
and automated testing frameworks. Experience with Python, Pandas, or ML libraries (e.g., Prophet, XGBoost, TensorFlow). Strong understanding of cloud infrastructure (AWS, GCP, or Azure). Excellent communication and cross-functional collaboration skills.
Seattle, WA ( need to travel once in 3-4 months) Salary - CAD 160 k - 175K (USD $150k)
Mandatory Skills : Airflow and SQL
About the Role This is a role that blends
technical leadership ,
product thinking , and
data-driven innovation . You'll lead a team of engineers in building full stack applications that integrate with , leverage
machine learning models , and deliver real-time insights to planners, merchandisers, and supply chain teams. Key Responsibilities
Lead full stack development
using technologies like Angular, React, Node.js, GraphQL, and cloud-native services (AWS/GCP). Design and build integrations
between Anaplan and internal systems to support planning, forecasting, and scenario modeling. Collaborate with data scientists
to operationalize ML models for demand forecasting, inventory optimization, and supply chain analytics. Develop intuitive tools
for planners and business users to interact with forecasts, adjust plans, and simulate outcomes. Establish and maintain CI/CD pipelines
using Gitlab to automate testing, deployment, and monitoring. Mentor engineers
and promote best practices in architecture, testing, and DevOps. Champion strong engineering practices , including:
Test-driven development (TDD) Code reviews and pair programming Scalable architecture and modular design Observability, logging, and performance monitoring
Drive agile product development , working closely with Product, UX, and Planning teams to deliver high-impact features. Qualifications
9+ years of experience in software engineering,
with 2+ years in technical leadership role. Strong full stack development skills with modern frameworks (React, Next.js, Node.js). Familiarity with
AI/ML concepts , especially in time series forecasting, demand sensing, or optimization. Experience deploying ML models into production environments (e.g., using SageMaker, Vertex AI, or custom APIs). Proven experience implementing and managing
CI/CD pipelines
and automated testing frameworks. Experience with Python, Pandas, or ML libraries (e.g., Prophet, XGBoost, TensorFlow). Strong understanding of cloud infrastructure (AWS, GCP, or Azure). Excellent communication and cross-functional collaboration skills.