Full Stack Data Engineer

Role overview

Responsibilities

• Analyze legacy data structures, relationships, transformations, business rules, and connected platforms.
• Build ETL/ELT pipelines and support migration, conversion, source-to-target mapping, profiling, cleansing, validation, and reconciliation.
• Design and maintain 3NF, dimensional, and analytical models; build extracts, interfaces, feeds, and operational or analytical reports.
• Create automated controls for data completeness, record counts, financial totals, balances, and results.
• Partner with business and technical teams; investigate data issues and support root-cause analysis and remediation.
• Maintain pipeline scheduling, monitoring, alerting, restart, exception handling, lineage, mappings, specifications, and reconciliation evidence.
• Contribute to migration planning, test-data preparation, conversion rehearsals, parallel validation, cutover, and post-production stabilization.

Required qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field, or equivalent professional experience.
• 4+ years in data engineering, ETL development, data migration, or cloud data engineering; advanced SQL skills.
• Hands-on Informatica, Azure Data Factory, Databricks, or comparable ETL/ELT platform experience.
• Knowledge of data warehousing, 3NF, Medallion Architecture, dimensional modeling, and enterprise data models.
• Experience with migration, file-based integrations, data delivery, data-quality controls, financial reconciliation, and auditability.
• Reporting experience with Power BI, Tableau, SSRS, Crystal Reports, or similar tools; scheduling and orchestration experience.
• Strong analytical, troubleshooting, and communication skills.

Preferred qualifications

• Legacy-system modernization and complex data-conversion program experience is preferred.
• Exposure to Azure Databricks, Synapse, Spark, Python, or other modern cloud/data platforms is preferred.
• Git, CI/CD, automated deployment, DevOps, APIs, Kafka, Azure Event Hubs, and event-driven integration experience is preferred.
• Insurance, financial services, producer compensation, distribution technology, or AI/BI/Generative AI experience is an asset.

Work arrangement

• The working arrangement is hybrid.

Compensation

• The stated base salary range is CAD 86,100–136,100; incentive compensation may also be available.