{"id":4297728,"url":"https://alion.io/job/manulife-full-stack-data-engineer","title":"Full Stack Data Engineer","company":{"id":6650,"name":"Manulife","domain":"manulife.com","url":"https://alion.io/company/manulife","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":89,"open_postings":128,"ghost_share":0.039,"stale_share":0.219,"repost_share":0.18,"time_to_fill_p50_days":27,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada","Waterloo, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Cognos","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Informatica","optional":false},{"name":"MuleSoft","optional":false},{"name":"Power BI","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Apex","optional":true},{"name":"CI/CD","optional":true},{"name":"Git","optional":true},{"name":"Python","optional":true},{"name":"Rest API","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-13T00:00:00Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-14T02:06:20Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Manulife / John Hancock is seeking a highly skilled Full-Stack Data Engineer, Modernization & Migration to join our Insurance Licensing & Compensation Engineering team.\nThe successful candidate will play a key role in the migration of legacy licensing & compensation capabilities to vendor Platform & Data Lake.\nThis role will focus on analyzing and transforming complex legacy data, building scalable ETL/ELT pipelines, supporting data conversion and reconciliation, and developing the reports, extracts, and downstream feeds required to enable the future-state platform.\nThe ideal candidate combines strong SQL, Informatica/ADF/Data Bricks, data warehousing, data modeling, ETL, reporting, and data analysis skills with the ability to understand complex business rules and data relationships across legacy and modern platforms.\nPosition Responsibilities:\nAnalyze data structures, relationships, transformations, and business rules across multiple legacy systems, and related upstream and downstream platforms.\nDesign and develop ETL/ELT pipelines using Informatica, Azure Data Factory (ADF), SQL, or Databricks to support data conversion, integration, and downstream delivery.\nSupport the migration and conversion of data into the target compensation platform and the Data Lake.\nPerform source-to-target mapping, data profiling, cleansing, transformation, validation, and reconciliation throughout the migration lifecycle.\nDesign and maintain 3NF, dimensional, and analytical data models supporting business processing, reporting, reconciliation, and downstream consumption.\nBuild automated data extracts, interfaces, and feeds for Finance, Distribution, Operations, Treasury, and other enterprise consumers.\nDevelop operational, reconciliation, and analytical reporting using tools such as Power BI, Tableau, Cognos, SSRS, or Crystal Reports.\nDevelop automated controls to validate record counts, financial totals, balances, results, and source-to-target completeness.\nPartner with business analysts, engineers, architects, and Operations to translate legacy data structures and processing requirements into future-state solutions.\nInvestigate complex data issues across source systems, transformation layers, target vendor platform, and downstream consumers and support root-cause analysis and remediation.\nBuild and maintain scheduling, monitoring, alerting, restart, and exception-handling capabilities for production data pipelines.\nMaintain clear data lineage, mappings, transformation rules, technical specifications, and reconciliation evidence to support auditability and production readiness.\nContribute to migration planning, test-data preparation, conversion rehearsals, parallel validation, cutover, and post-production stabilization.\nRequired Qualifications:\nBachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a related field, or equivalent professional experience.\n4+ years of experience in data engineering, ETL development, data migration, Cloud data engineering.\nAdvanced SQL skills with experience analyzing and transforming large and complex datasets.\nStrong hands-on experience with Informatica, Azure Data Factory (ADF), Data Bricks or comparable ETL/ELT platforms.\nStrong working knowledge of data warehousing, 3NF, Medallion Architecture, dimensional modeling, and enterprise data-model design.\nWork experience with large-scale data migration or system-conversion initiatives, including source-to-target mapping, profiling, transformation, validation, and reconciliation.\nExperience building automated extracts and file-based integrations, including CSV, TSV, XML, JSON, or similar formats.\nExperience delivering data through SFTP, Managed File Transfer (MFT), APIs, or enterprise integration frameworks.\nStrong experience implementing data-quality controls, financial reconciliation, exception handling, data governance and auditability.\nPractical experience developing operational or analytical reporting using Power BI, Tableau, SSRS, Crystal Reports, or similar technologies.\nExperience with scheduling and orchestration technologies such as ADF, CA WLA or MuleSoft.\nStrong analytical and troubleshooting skills with the ability to reverse-engineer complex legacy data structures and transformation logic.\nStrong communication skills with the ability to work across engineering, architecture, operations, and business teams.\nPreferred Qualifications:\nExperience with legacy-system modernization and complex data-conversion programs.\nExposure to Azure Databricks, Synapse, Spark, Python or other modern cloud/data platforms.\nExperience with Git, CI/CD pipelines, automated deployment, and DevOps practices for data engineering workloads.\nFamiliarity with REST APIs, API gateways, Kafka, Azure Event Hubs, or event-driven integration patterns.\nBackground in insurance, financial services, producer compensation, or distribution technology would be a strong asset.\nStrong communication, analytical, problem-solving skills.\nExperience with AI, Business Intelligence (BI), and/or Generative AI solutions.\nWhen you join our team:\nWe’ll empower you to learn and grow the career you want.\nWe’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.\nAs part of our global team, we’ll support you in shaping the future you want to see.\nThe role being advertised is an existing vacancy.\nAbout Manulife and John Hancock\nManulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.\nManulife is an Equal Opportunity Employer\nAt Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.\nIt is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact .\nReferenced Salary Location\nToronto, OntarioWorking Arrangement\nHybridBase salary range is expected to be between\n$86,100.00 CAD - $136,100.00 CADEmployees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual base salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact  for the salary range for your location.\nManulife offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence. If you are applying for this role in the U.S., please contact  for more information about U.S.-specific paid time off provisions.\nWe use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. 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