Data Operations Analyst

at  Manulife

We are a leading financial services provider committed to making decisions easier and lives better for our customers and colleagues around the world. From our environmental initiatives to our community investments, we lead with values throughout our business. To help us stand out, we help you step up, because when colleagues are healthy, respected and meaningfully challenged, we all thrive. Discover how you can grow your career, make impact and drive real change with our Winning Team today.

JOB DESCRIPTION

Join our Insurance Engineering and Analytics team!
As a Data Operations Analyst , you will conduct assessment of data related issues, support automation of data processes and ensure the ongoing steady-state execution of data pipelines in production.

SKILLS AND EXPERIENCE:

• Minimum 5 years+ of related experience preferred.
• Good understanding of relational and warehousing database technology working with SQL Server and Azure SQL.
• Proficiency in SQL Server monitoring tools (e.g., for data pipelines and systems) and the ability to query log reports.
• Proficiency in Python, shell or any other scripting language for data querying, manipulation and analysis.
• Experience writing SQL queries and stored procedures.Experience in the insurance domain is a bonus.

Nice to haves :

• Experience with workload automation.
• Familiarity SSRS, SSIS and SSAS.

• Familiarity with Azure cloud platform.Knowledge of ML concepts.

• Performs data and system analysis, conducts assessment of complex data related issues, identifies root cause, and resolves issues and course corrects as required.
• Maintains comprehensive documentation of processes, information flows, anomalies, and resolutions for reference and compliance.
• Supports automation of data processes on on-premise and cloud(if applicable) to ensure secure, supported and scalable solutions.
• Investigates root cause of identified data issues and supports data owners in development and implementation of remediation plans.
• Assists with conducting regular audits and assessments of data management processes and controls.
• Collaborates with team on data efforts and works with complex (type, quality, volume) and unfamiliar data.
• Identifies potential areas of optimization based on analysis of data.