Lead AI & Analytics Engineer

Lorven Technologies Inc. is looking for a Lead Engineer to build and maintain scalable data pipelines and data platforms that support analytics, business intelligence, reporting, and AI initiatives. In this hands-on engineering role, you will design efficient data pipelines and improve data infrastructure while collaborating with various stakeholders to ensure high-quality data availability across the organization.

Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows to ingest and transform data from multiple sources
• Develop and optimize batch and near real-time data processing pipelines for analytics and reporting
• Build and maintain data warehouse and data lake structures to support business intelligence and analytics use cases
• Implement and maintain data models that support efficient querying and reporting
• Improve performance and scalability of data systems through query optimization, indexing, and partitioning strategies
• Implement data quality checks, monitoring, and logging to ensure reliability of data pipelines
• Exposure to AI initiatives and experience building data pipelines supporting AI workflows
• Work with data architects and engineering teams to implement scalable data platform designs
• Collaborate with analysts, BI developers, and business stakeholders to deliver data solutions that support business needs
• Maintain documentation for data pipelines, data models, and data workflows

Requirements:

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows to ingest and transform data from multiple sources
• Develop and optimize batch and near real-time data processing pipelines for analytics and reporting
• Build and maintain data warehouse and data lake structures to support business intelligence and analytics use cases
• Implement and maintain data models that support efficient querying and reporting
• Improve performance and scalability of data systems through query optimization, indexing, and partitioning strategies
• Implement data quality checks, monitoring, and logging to ensure reliability of data pipelines
• Exposure to AI initiatives and experience building data pipelines supporting AI workflows
• Work with data architects and engineering teams to implement scalable data platform designs
• Collaborate with analysts, BI developers, and business stakeholders to deliver data solutions that support business needs
• Maintain documentation for data pipelines, data models, and data workflows