Job Title: Enterprise Datalake Product Owner
Location: Canada Remote
Contract: 6 Months
Client Domain: HRMS (Human Resource Management System) applications for public sector organizations
Key Responsibilities:
- Own the delivery and execution of a new enterprise data lake on Snowflake or Databricks from initial setup through production rollout.
- Translate high-level business and data requirements into clear actionable technical stories and sprint plans for the engineering team.
- Define and drive data ingestion and integration pipelines from core SaaS applications and supporting enterprise systems.
- Partner closely with data engineers and architects to design data models storage layers and performance optimization strategies.
- Manage the end-to-end development lifecycle ensuring milestones dependencies and deliverables are met on schedule.
- Prioritize backlog items based on business impact technical feasibility and cross-team dependencies.
- Build and maintain a detailed execution roadmap for phased delivery including MVP and incremental enhancements.
- Coordinate with infrastructure and DevOps teams to establish reliable scalable and cost-efficient cloud environments.
- Define and track operational KPIs such as data pipeline success rates processing latency and platform uptime.
- Ensure smooth handoffs documentation and operational readiness for analytics and data science consumers.
Job Title: Enterprise Datalake Product Owner Location: Canada Remote Contract: 6 Months Client Domain: HRMS (Human Resource Management System) applications for public sector organizations Key Responsibilities: Own the delivery and execution of a new enterprise data lake on Snowflake or ...
Job Title: Enterprise Datalake Product Owner
Location: Canada Remote
Contract: 6 Months
Client Domain: HRMS (Human Resource Management System) applications for public sector organizations
Key Responsibilities:
- Own the delivery and execution of a new enterprise data lake on Snowflake or Databricks from initial setup through production rollout.
- Translate high-level business and data requirements into clear actionable technical stories and sprint plans for the engineering team.
- Define and drive data ingestion and integration pipelines from core SaaS applications and supporting enterprise systems.
- Partner closely with data engineers and architects to design data models storage layers and performance optimization strategies.
- Manage the end-to-end development lifecycle ensuring milestones dependencies and deliverables are met on schedule.
- Prioritize backlog items based on business impact technical feasibility and cross-team dependencies.
- Build and maintain a detailed execution roadmap for phased delivery including MVP and incremental enhancements.
- Coordinate with infrastructure and DevOps teams to establish reliable scalable and cost-efficient cloud environments.
- Define and track operational KPIs such as data pipeline success rates processing latency and platform uptime.
- Ensure smooth handoffs documentation and operational readiness for analytics and data science consumers.
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