Lead Data Engineer (Planning & Forecasting | Kafka | Snowflake | AWS | GitLab CI/CD)
Location: Vancouver, BC (Hybrid)
Type: Full-Time / Direct Hire
Salary: Let's Discuss
Work Authorization: Must be authorized to work in Canada without sponsorship
Non Negotiable Tech : Airflow,
About the Role
We are looking for a Lead Data Engineer to design and build scalable data platforms and services that power planning, forecasting, and scenario modeling initiatives. This role will work closely with Product, UX, and Planning teams to deliver high-impact tools that enable planners and business stakeholders to interact with forecasts, adjust plans, and simulate business outcomes.
You will be a hands-on technical leader who drives engineering excellence across architecture, performance, CI/CD, and observability, while mentoring and guiding other engineers.
Key Responsibilities
• Design, build, and maintain scalable data architecture and integrations across internal systems to support planning, forecasting, and scenario modeling
• Develop and support streaming data pipelines using Kafka and related event-streaming patterns
• Build reliable and maintainable pipelines using strong ETL/ELT, SQL, and data modeling principles
• Work with cloud data platforms such as Snowflake, orchestration tools like Airflow, and databases such as Postgres
• Operationalize machine learning models used for:
• Demand forecasting
• Inventory optimization
• Supply chain analytics
• Develop intuitive data products and tooling that allow planners/business users to:
• View forecasts and insights
• Adjust assumptions and plans
• Run scenario simulations and compare outcomes
• Establish and maintain GitLab CI/CD pipelines for automated testing, deployment, monitoring, and release management
• Ensure systems are production-ready with strong logging, monitoring, alerting, and performance optimization
• Drive agile delivery with cross-functional teams (Product, UX, Planning, Engineering)
• Mentor engineers and promote best practices across architecture, testing, and DevOps
Engineering Practices We Value
• Test-driven development (TDD) and automation-first mindset
• Strong code review culture and collaborative engineering (pair programming when needed)
• Scalable architecture with modular and reusable design patterns
• Observability-first systems (logging, monitoring, dashboards, performance tuning)
Required Qualifications
• 12+ years of software engineering experience, including 2+ years in a technical leadership role
• Strong hands-on experience as a Data Engineer / Data Platform Engineer
• Experience with streaming frameworks such as Kafka
• Strong skills in SQL, ETL/ELT, data warehousing, and data modeling
• Hands-on experience with one or more of the following:
• Snowflake
• Airflow
• Postgres
• (or similar cloud-native data tools)
• Proven experience implementing and managing CI/CD pipelines and automated testing frameworks (GitLab preferred)
• Strong understanding of cloud infrastructure (AWS, GCP, or Azure)
• Excellent communication skills with the ability to work effectively across teams and stakeholders
Nice to Have
• Anaplan model building / model development experience
• Experience building data solutions for planning, forecasting, supply chain, or retail/CPG domains
• Exposure to MLOps tools or production ML deployment practices
• Experience coordinating across offshore/onshore teams
Education
Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent practical experience)
Core Skills / Keywords
Kafka | Airflow | Snowflake | SQL | Postgres | ETL/ELT | Data Warehousing | Data Modeling | AWS | GitLab CI/CD | Observability | Forecasting | Scenario Modeling | Supply Chain Analytics | Leadership
