Snowflake Lead
Job Desc: Onsite Team Lead – Data Engineering (Snowflake) :
Location : Canada remote
**Must have 10+ years of experience**Team Lead with strong hands-on expertise in Snowflake, Python, and AWS to design and deliver end-to-end data pipelines using Snowflake Native Apps / Snowpark Container Services (SPCS). The ideal candidate will combine deep technical expertise with strong business engagement skills, owning delivery end-to-end while leading offshore teams and ensuring high-quality execution, while also exploring modern capabilities like GenAI within Snowflake
.Required Skills and Experienc
- eStrong hands-on expertise in Snowflake, SPCS, Python, and AW S (e.g., S3, Lambda, Glue, Step Functions)
- .Deep understanding of Snowflake data modeling, table design, task orchestration, and performance tuning
- .Experience with CI/CD practices and deployment automation for data platforms
- .Strong knowledge of data security, governance, and access control (RBAC) in Snowflake
- .Proven experience handling multiple data sources (e.g., email, data shares, FTP/SFTP, APIs) and managing schema evolution
- .Strong focus on data quality, validation frameworks, and data governance
- .Experience in working directly with business stakeholders and translating requirements into technical designs
- .Proven ability to debug and resolve production issues in a fast-paced environment
- .Strong leadership to guide offshore team on daily deliverables, review and take ownership of end-to-end delivery
- .Experience with Agile/Scrum methodologies and sprint planning
- .Detail-oriented with a strong eye for optimization and continuous improvement
- .Exposure to Snowflake Cortex, Snowflake AI functions, or similar GenAI/ML capabilities
- .Exposure to cloud-based data architecture and integration patterns
- sCollaborate closely with business stakeholders to gather, analyze, and refine data requirements, and translate them into scalable technical solutions
- .Act as the primary point of contact for business/client stakeholders, ensuring proactive communication, issue resolution, and expectation management
- .Own end-to-end delivery from requirement gathering through design, development, deployment, and production support
- .Design and build scalable data pipelines using Python, Snowflake, and AWS services
- .Ingest and integrate data from multiple sources such as email feeds, Snowflake data shares, FTP/SFTP, APIs, and other upstream systems
- .Architect and optimize Snowflake data models, tables, tasks, and data processing workflows
- .Optimize Snowflake workloads for performance and cost efficiency (query tuning, clustering, warehouse sizing, caching strategies)
- .Implement and manage CI/CD pipelines for data workflows and Snowflake deployments
- .Ensure data security, governance, and access control (RBAC) within Snowflake environments
- .Set up monitoring, alerting, and observability for data pipelines and production systems
- .Handle and integrate multiple data sources with varying structures, ensuring consistency and reliability
- .Manage evolving data schemas and ensure minimal disruption to downstream systems
- .Ensure strong data quality, validation, and governance across pipelines
- .Troubleshoot and resolve production issues rapidly with strong root-cause analysis and innovative solutions
- .Provide clear directions to offshore team on deliverables, timelines, and implementation approach
- .Review code, enforce best practices, and ensure high standards of quality and maintainability
- .Lead sprint planning, estimation, and delivery tracking
- .Explore and implement new Snowflake features such as Disaster Recovery, Archival Policies, Cortex services, and Snowflake AI functions
- .Identify and drive use cases leveraging GenAI capabilities within Snowflake for data enrichment, automation, or insights generation
- .Continuously identify opportunities for performance, cost, and process optimization