At a glance
Automatically prepared from the listing. Check the original description for the full requirements.
Jump to the original descriptionResponsibilities
Lead end-to-end enterprise-scale cloud data migration strategies, including scoping, planning, and production cutover. Design and optimize high-performance ETL pipelines using Azure Databricks and Azure Data Factory while establishing rigorous data quality frameworks.
Requirements
Requires strong expertise in Azure ecosystem tools like PySpark and Delta Lake for large-scale data movement. Candidates must be able to bridge the gap between technical engineering teams and business stakeholders to ensure secure and accurate migrations.
Working hours
40 hours per week
Skills
- Data Migration
- QA
- Data Validation
- Microsoft Azure
- Azure Databricks
- Azure Data Factory
- ETL
- PySpark
- Delta Lake
- Medallion Architecture
- Source-to-Target Mapping
- Data Profiling
- SIT
- UAT
- Regression Testing
- Data Reconciliation
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Consulting
- Software
- Management & Leadership
Keywords
- Data Migration
- Azure Databricks
- Azure Data Factory
- PySpark
- Delta Lake
- Medallion Architecture
- ETL
- ELT
- S2T Mapping
- Data Profiling
- Data Cleansing
- Deduplication
- Survivorship
- SIT
- UAT
- Regression Testing
- Cloud Migration
- Data Quality
- Reconciliation
- Enterprise Scale
- Information Technology
- IT Consulting
Original job description
We are seeking a highly skilled Data Migration Lead with strong QA and data validation expertise to drive our enterprise-scale cloud data migration initiatives. In this role, you will lead the end-to-end strategy, execution, and quality assurance of complex data migration tracks. You will leverage the Microsoft Azure ecosystem, specifically Azure Databricks and Azure Data Factory (ADF), to design high-performance ETL pipelines while establishing rigorous source-to-target reconciliation and automated data quality frameworks. The ideal candidate acts as the bridge between technical data engineering teams and business stakeholders, ensuring that data is migrated securely, accurately, and with zero business disruption.
Key Responsibilities
Migration Strategy & Leadership: Lead end-to-end data migration tracks from initial scoping, legacy profiling, and planning through production cutover and deployment.
Define comprehensive migration strategies, source-to-target mapping (S2T) documents, and fallback/rollback procedures.
Coordinate with cross-functional stakeholders, including product owners, system architects, and business teams, to align on migration criteria and business logic.
ETL Engineering & Orchestration: Design and optimize ETL/ELT pipelines to ingest, transform, and load massive scale datasets from disparate legacy systems into Azure Cloud.
Build optimized migration frameworks inside Azure Databricks using PySpark, Delta Lake, and Medallion architecture patterns.
Orchestrate complex workflows and data movements via Azure Data Factory, managing incremental loads, scheduling, and error handling.QA, Data Quality & Reconciliation
Establish the data validation framework, implementing rules for advanced data profiling, cleansing, deduplication, and survivorship.
Author comprehensive test strategies encompassing System Integration Testing (SIT), User Acceptance Testing (UAT), regression testing, and final production validation.
Build automated source-to-target reconcilia
