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Job Description & How to Apply Below
The Lead Data Engineer will lead complex data migration and modernization initiatives on the Azure platform for enterprise clients. This role focuses on reverse-engineering legacy data systems, analyzing end-to-end data lineage, and redesigning ETL/ELT pipelines to support simplified, scalable, and compliant Azure-based data architectures. The role requires strong hands-on engineering expertise, technical leadership, and the ability to operate effectively in ambiguous, under-documented environments.
Key Responsibilities
Lead enterprise data modernization and cloud migration initiatives using Microsoft Azure
Reverse-engineer complex, undocumented legacy ETL pipelines to extract business and transformation logic
Analyze, document, and validate end-to-end data lineage across multi-layer data architectures
Design simplified Azure-based data architectures that reduce unnecessary layers while preserving business logic and regulatory requirements
Lead end-to-end data pipeline development from source systems through staging, curated, and analytical layers
Build and optimize ETL/ELT workflows using Azure-native and enterprise data integration tools
Conduct gap analysis and technical feasibility assessments to support modernization and regulatory reporting initiatives
Collaborate with data architects, engineers, and business stakeholders to ensure scalable, maintainable Azure solutions
Provide technical leadership across multiple concurrent data initiatives, ensuring delivery quality and architectural consistency
Mentor data engineering teams and establish best practices for Azure data engineering, CI/CD, and data transformation workflows
Create and maintain technical documentation, including data flow diagrams, mapping specifications, lineage documentation, and operational runbooks
Required Qualifications
7+ years of experience in data engineering with strong ETL/ELT development expertise
Hands-on experience with enterprise ETL tools such as IBM Data Stage, Informatica, SSIS, Talend, or equivalent
Strong experience with Azure data services, including:
Azure Data Factory / Synapse Pipelines
Azure Synapse Analytics (Dedicated or Serverless SQL Pools)
Azure Data Lake Storage (ADLS Gen2)
Proven ability to reverse-engineer undocumented legacy systems and extract embedded business logic
Expert-level SQL skills and strong experience with relational databases (SQL Server, Oracle, Postgre
SQL, or similar)
Solid understanding of data warehousing concepts, dimensional modeling, and regulatory reporting requirements
Demonstrated ability to trace and document data lineage across complex, multi-system architectures
Proficiency in Python or similar scripting languages for automation and analysis
Strong documentation and communication skills, with the ability to translate technical concepts for business stakeholders
Self-starter comfortable working in ambiguous environments with limited documentation
Preferred Qualifications
Experience with Azure Dev Ops, CI/CD pipelines, and Infrastructure as Code (ARM, Bicep, or Terraform)
Familiarity with Azure Purview / Microsoft Purview for data governance and lineage
Experience migrating on-premise ETL platforms to Azure-native services
Prior experience in regulated industries (financial services, insurance, healthcare)
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