The Lead Data Engineer position at Manulife offers an exciting opportunity to be at the forefront of building and enhancing data capabilities, aligning with our mission to become a digital customer leader. This role is crucial in implementing, optimizing, and maintaining data assets that drive strategic business decisions. By joining our team, you will have the chance to mentor and lead a high-performing team, stay updated with the latest technologies, and contribute to a collaborative and innovative work environment.

REQUIRED QUALIFICATIONS:

• 10+ years of experience as a Data Engineer.
• Bachelor’s Degree in Computer Science, Information Technology, or a related field.
• Understanding of Azure infrastructure and security principles and proven experience with Azure Data Factory, Databricks, Python/PySpark, Java, Scala.
• Knowledge of Azure Data Lake Storage (ADLS Gen2) and its topology on blob storage with file hierarchy, storage account, containers, and folders.
• Proficient in data mart fact and dimension design concepts, ETL\ELT , implementing with Python, PySpark, store procedures, SQL in ADLS with Lakehouse architecture using Databricks or in Azure Synapse with Dedicated SQL pool.
• Understanding of integrations with Azure AD and Azure security principles (user group, service principal, managed identity), network concepts (VNet, Subnet, NSG rules, private endpoints), password\credential\key management and data protection.

PREFERRED QUALIFICATIONS:

• Experience with LLM and AI tools.
• Proficiency in using Unity Catalog.
• Experience with Power BI for data modeling and reporting.
• Strong problem-solving skills and technical issue resolution.
• Excellent communication skills for collaboration with diverse teams.

• Mentor and coach data engineers, fostering a high-performing team culture.
• Design, develop, and manage scalable data pipelines for diverse data sources.
• Collaborate with cross-functional teams to design accurate data schemas.
• Continuously optimize ETL processes for efficiency and real-time processing.
• Ensure data quality through rigorous testing and validation mechanisms.
• Deploy and integrate Azure Data Services (ADF, Databricks) using DevOps tools and principles: GitHub Repository, Jenkins CI\CD pipelines, integrated unit tests