Data Migration Lead || Toronto, ON - Hybrid || Fulltime FTE

Data Migration Lead

Location: Toronto, ON
Work Arrangement: Hybrid



Employment Type: Fulltime FTE - Permanent

Experience: 8 10 Years

Job Summary: We are seeking a highly skilled Data Migration Lead with strong expertise in QA, data validation, reconciliation, ETL/ELT, and cloud data migration . The successful candidate will lead end-to-end enterprise data migration initiatives, leveraging Microsoft Azure, Azure Databricks, Azure Data Factory (ADF), PySpark, Delta Lake, and Medallion Architecture . This role will act as a key bridge between data engineering teams, technical stakeholders, and business teams , ensuring data is migrated securely, accurately, efficiently, and with minimal business disruption.

Key Responsibilities

Migration Strategy & Leadership

• Lead end-to-end data migration initiatives from discovery, source profiling, planning, mapping, and development through production cutover .

• Define comprehensive migration strategies, Source-to-Target (S2T) mappings , migration plans, and rollback/fallback procedures.

• Collaborate with Product Owners, Solution Architects, Data Engineers, QA teams, and business stakeholders.

• Define migration scope, success criteria, business rules, and validation requirements.

ETL Engineering & Orchestration

• Design, develop, and optimize high-volume ETL/ELT pipelines for migrating data from legacy platforms to Azure Cloud.

• Build migration frameworks using Azure Databricks, PySpark, Delta Lake, and Medallion Architecture .

• Develop and optimize data transformation and processing logic using Python/PySpark .

• Orchestrate data workflows using Azure Data Factory (ADF) .

• Implement incremental loads, scheduling, dependency management, monitoring, and error handling.

• Optimize pipelines for performance, scalability, reliability, and cost efficiency.

QA, Data Quality & Reconciliation

• Establish comprehensive data quality and validation frameworks for migration projects.

• Perform data profiling, cleansing, deduplication, standardization, and survivorship analysis.

• Define and execute SIT, UAT, regression testing, and production validation strategies.

• Develop automated Source-to-Target reconciliation processes.

• Validate record counts, data completeness, transformations, business rules, and data integrity.

• Identify, troubleshoot, and resolve data discrepancies and migration defects.

Production & Stakeholder Management

• Lead migration cutover, deployment, reconciliation, and post-production validation activities.

• Develop migration dashboards, reports, status updates, and quality metrics.

• Manage migration risks, issues, dependencies, and remediation plans.

• Ensure migration activities follow enterprise security, governance, compliance, and data management standards .

• Communicate effectively with both technical and non-technical stakeholders.

Required Technical Skills

• Azure Databricks

• Azure Data Factory (ADF)

• PySpark / Python

• Delta Lake

• Medallion Architecture

• ETL / ELT

• Data Migration

• Source-to-Target (S2T) Mapping

• Data Reconciliation & Validation

• Data Quality / Data Profiling

• Data Cleansing & Deduplication

• SIT / UAT / Regression Testing

• SQL

• Cloud Data Engineering

• Migration Cutover & Production Validation

Preferred Qualifications

• 8 10 years of experience in data migration, data engineering, ETL, QA, or data validation .

• Strong experience leading enterprise-scale cloud migration initiatives.

• Hands-on experience with Azure data services and large-scale data processing .

• Strong understanding of data migration methodologies, reconciliation, and quality assurance.

• Experience working with legacy systems and disparate data sources.

• Excellent analytical, problem-solving, communication, and stakeholder management skills.

• Ability to lead complex migration tracks independently and drive successful production outcomes.

Key Skills / Keywords

Data Migration Lead, Data Migration, Azure, Azure Databricks, Azure Data Factory, ADF, PySpark, Python, Delta Lake, Medallion Architecture, ETL, ELT, SQL, Data Engineering, Data Quality, Data Validation, Data Reconciliation, Source-to-Target Mapping, S2T, Data Profiling, Data Cleansing, Deduplication, Survivorship, SIT, UAT, Regression Testing, Production Validation, Migration Cutover, Cloud Migration, Azure Cloud.