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CloudLabs Inc is looking for an experienced Data Warehouse Technical Project Manager to drive end-to-end delivery of enterprise data projects and modern data platforms. You will coordinate data engineering, modeling, BI, QA, and business stakeholders to deliver scalable solutions.
The role requires strong PM, data engineering knowledge, stakeholder management, and technical leadership to deliver high-quality results within scope and timelines.
CloudLabs Inc was founded in 2014 with the mission to provide exceptional IT & Business consulting services at a competitive price, to help clients realize the best value from their investments. Within a short span, CloudLabs evolved from pure-play consulting into a transformative partner for Business Acceleration Advisory, Transformative Application Development & Managed Services - enabling digital transformations, M&A transitions, Automation & Process-driven optimizations & complex Integration initiatives for enterprises across the globe. As a Strategic Planning & Implementation Partner for global companies, CloudLabs has seen a 200% uptake in winning high-value, high-impact and high-risk projects that are critical for the business.
With offices in the US, Canada, & India and with the team of 250+ experienced specialists, CloudLabs is now at an inflection point and ready for its next curve of progress.
Minimum 10-15 years of Experience overall experience & Project Manager 5 - 7 years
Snowflake, dbt, ETL design, AWS
Fulltime or Permanent
Either Canadian citizens or PR Holder
Candidates in EST or CST time zones only
Data & Analytics
We are looking for an experienced Data Warehouse Technical Project Manager to lead end-to-end delivery of enterprise data warehouse and modern data platform initiatives. The role requires a strong combination of project management, data engineering knowledge, stakeholder management, and technical delivery leadership.
The candidate will be responsible for managing cross-functional teams across data engineering, data modeling, BI, QA, and business stakeholders to deliver scalable, high-quality data solutions within agreed timelines, budgets, and scope.