Data Engineer

We are looking for a Data Engineer to join the Global Technology team at MBPS, supporting the design, development, and operation of enterprise data platforms across GWAM. This role is primarily focused on building and modernizing scalable data solutions using Microsoft Azure Data & Analytics technologies, including Azure Databricks, Azure Data Factory, Azure Data Lake, and Azure SQL. Working within an Agile, high-performing environment, the successful candidate will be responsible for delivering robust data pipelines, data integration solutions, automation, and analytics capabilities that enable business insights and data-driven decision-making. In addition to data engineering responsibilities, the role will provide Level 2/3 support for data platforms and critical applications, including troubleshooting data quality issues, pipeline failures, production incidents, and system integrations. The ideal candidate will bring strong analytical and problem-solving skills, a customer-focused mindset, and experience collaborating with business and technology teams to deliver reliable, scalable, and well-governed data solutions that align with Manulife's enterprise standards and strategic objectives.

Position Responsibilities:

• Design, develop, and maintain batch and real-time data pipelines using Microsoft Azure Data & Analytics services, including Azure Data Factory, Azure Databricks, Azure Data Lake, and Azure SQL.
• Build, optimize, and support scalable data ingestion, transformation, curation, and delivery processes across enterprise data platforms.
• Design and develop ETL/ELT processes using Azure Data Factory, Databricks, PySpark, SQL, Python, and related data engineering technologies.
• Develop and maintain modern data architectures, data warehouses, data marts, and relational/non-relational databases supporting reporting, analytics, and data science initiatives.
• Design, build, and maintain data services, APIs, and reusable datasets for business and technology consumers.
• Translate business requirements into scalable technical solutions while collaborating with business users, architects, developers, and business analysts.
• Lead and contribute to the modernization of enterprise data solutions using Azure cloud technologies and best practices.
• Develop and maintain CI/CD pipelines and DevOps processes using GitHub, Azure DevOps, Jenkins, and related automation tools.
• Prepare, transform, and expose data for reporting, advanced analytics, machine learning, and visualization platforms such as Power BI.
• Monitor, troubleshoot, and optimize performance, reliability, scalability, and operational efficiency of data platforms and pipelines.
• Provide Level 2/3 support for enterprise applications, data platforms, and integrations ensuring adherence to service level commitments.
• Investigate and resolve incidents involving data pipelines, data quality, batch processing, file transfers, APIs, and application-related issues.
• Perform root cause analysis on production incidents and coordinate with development teams on defect resolution and minor enhancements.
• Investigate feed/file delivery failures, workflow issues, and scheduling concerns using tools such as Azure Data Factory, Databricks, CA Workload Automation (or equivalent), ServiceNow, and Jira.
• Analyze and resolve data discrepancies, reconciliation issues, and data quality concerns in partnership with business stakeholders.
• Participate in Incident, Problem, Change, and Release Management activities following ITIL and DevSecOps practices.
• Create and maintain technical documentation, operational procedures, knowledge articles, and support runbooks.
• Develop reports, dashboards, and process automations using Power BI, Power Automate, Power Apps, or similar tools.
• Track operational metrics, identify continuous improvement opportunities, and recommend automation and process optimization initiatives.
• Mentor junior team members, conduct code reviews, support knowledge transfer activities, and contribute to a culture of continuous learning and collaboration.
• Remain current on industry standards, emerging technologies, methodologies, and enterprise best practices.
• Perform other duties and responsibilities as assigned by management.

Required Qualifications:

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• Minimum 2 years of experience in Data Engineering, Data Warehousing, ETL/ELT development, or related data-focused roles.
• Strong hands-on experience with Microsoft Azure Data Platform technologies (Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage (ADLS), Azure SQL Database)
• Strong experience designing, developing,