Data Warehouse Technical Project Manager

About CloudLabs:

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.

Please write & follow us here:

Website: cloudlabsit.com

LinkedIn: CloudLabs Inc

Email us: info@cloudlabsit.com

What we offer:

• We welcome candidates rejoining the workforce after career break/parental leave and support their journey to reacclimatize too corporate.
• Flexible remote work.
• Opportunity to work remotely is available.

Experience Required: Minimum 10-15 years of Experience

Required Technical Skills: Snowflake, dbt, ETL design, AWS

Job Location: Canada - Remote

Job Type: Fulltime or Permanent or Contract

VISA Status: Either Canadian citizens

Time zone Preferred: Candidates in EST or CST time zones only

Department: Data & Analytics

Position Overview:

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.

Key Responsibilities:

Project & Program Management:

• Lead end-to-end delivery of data warehouse and data engineering projects, from requirement gathering and planning through deployment and production support.
• Develop project plans, timelines, milestones, resource plans, budgets, and delivery schedules.
• Manage project scope, risks, dependencies, issues, and change requests.
• Drive Agile/Scrum ceremonies, sprint planning, daily stand-ups, sprint reviews, and retrospectives.
• Track project KPIs, delivery progress, resource utilization, and financial performance.
• Manage multiple workstreams and geographically distributed teams across US and offshore locations.

Data Warehouse Technical Leadership:

• Understand enterprise data warehouse architectures, data integration patterns, ETL/ELT pipelines, and modern cloud data platforms.
• Work closely with data architects and technical leads to translate business requirements into technical deliverables.
• Oversee data ingestion, transformation, data modeling, data quality, and reporting workstreams.
• Review high-level solution designs, source-to-target mappings, data models, and technical implementation plans.
• Identify technical risks related to data volume, performance, scalability, data reconciliation, and system integration.
• Coordinate data migration, testing, deployment, and production cutover activities.

Stakeholder & Client Management:

• Serve as the primary point of contact for client stakeholders, business leaders, and technical teams.
• Conduct project governance meetings, steering committee presentations, and executive status reviews.
• Manage stakeholder expectations, communicate delivery risks, and drive timely decision-making.
• Convert business requirements into actionable technical tasks and delivery milestones.
• Build strong client relationships and identify opportunities for additional data and analytics initiatives.

Team & Delivery Management:

• Lead and mentor data engineers, data modelers, QA engineers, business analysts, and technical leads.
• Manage resource allocation, capacity planning, onboarding, and utilization.
• Ensure adherence to engineering standards, development methodologies, documentation, and quality processes.
• Drive continuous improvement in delivery efficiency, automation, and engineering productivity.