Team Lead, Data Engineering

About The Opportunity

IntePros is partnering with a rapidly growing, technology-driven organization to identify a Team Lead, Data Engineering to support the design and evolution of their enterprise data platform.

This role sits at the intersection of data engineering and architecture, with a focus on building scalable, cloud-native data solutions that power analytics and AI-driven initiatives. The individual will play a key role in shaping data strategy, driving best practices, and mentoring a team of engineers.

Key Responsibilities

• Lead the design and implementation of scalable data architectures supporting operational, analytical, and AI/ML workloads
• Architect and optimize cloud-based data solutions across modern platforms (AWS, Azure, or GCP)
• Define and enforce data modeling standards, including dimensional, denormalized, and AI-friendly schema design
• Oversee the development of transformation layers using DBT, ensuring modular, well-documented, and testable data models
• Design and guide data integration and orchestration patterns using tools such as Airflow or similar frameworks
• Establish data quality standards, validation processes, and monitoring to ensure data integrity across pipelines
• Drive data governance initiatives including lineage, cataloging, access control, and metadata management
• Collaborate cross-functionally with engineering, product, and analytics teams to translate business requirements into scalable data solutions
• Mentor and develop data engineering team members, providing guidance on architecture, modeling, and best practices
• Support CI/CD processes and ensure efficient deployment and management of data pipelines

Qualifications

• 7+ years of experience in data engineering, data architecture, or related roles
• Proven experience designing and implementing cloud-based data platforms
• Strong SQL expertise and experience working with large-scale data environments
• Hands-on experience with ETL/ELT pipelines and orchestration tools (Airflow, Prefect, or similar)
• Experience with DBT for data transformation, testing, and documentation
• Strong understanding of data modeling techniques, including dimensional and OLAP/OLTP design
• Experience working with modern data warehouses such as Snowflake, Redshift, or BigQuery
• Familiarity with data governance, data quality frameworks, and metadata management
• Experience supporting downstream analytics or AI/ML use cases is a plus

Preferred Experience

• Python development (Pandas, PySpark)
• Experience with containerization (Docker, Kubernetes) and CI/CD automation
• Exposure to event-driven architectures or streaming data pipelines
• Experience with Databricks or similar platforms

No sponsorship for this role. Candidates must be Canadian Permanent Residents.