Principal Data Engineer with Migration experience

Job Tile : Principal Data Engineer with Migration experience

Location : Houston, Texas, USA, 77072 Hybrid

Duration : Long Term Contract

Position Overview

The Principal Data Engineer will also provide technical leadership for the migration of the existing Azure data platform to AWS, including workloads currently using Azure Data Factory (ADF), Azure Data Lake Storage Gen2 (ADLS Gen2), Databricks, and PostgreSQL/SQL Server. The role will define the target AWS architecture, migration approach, service mappings, integration patterns, security model, and operational standards. Databricks will remain a strategic data processing and transformation platform, while Azure-native data services will be transitioned to appropriate AWS capabilities.

Key Accountabilities

• Define and maintain the enterprise data and database strategy, including principles, standards, reference architectures, target-state roadmaps, measurable outcomes, ownership models, and architecture decision criteria for Aurora PostgreSQL topology, resilience, security, observability, and cost optimization.
• Lead assessment and migration of the existing Azure data platform to AWS, including ADF pipelines, ADLS Gen2 storage, Databricks workloads, database dependencies, security configurations, monitoring, scheduling, and downstream integrations.
• Define the Azure-to-AWS target-state architecture, including appropriate migration patterns such as ADLS Gen2 to Amazon S3, Azure database workloads to Amazon Aurora PostgreSQL, and ADF orchestration to appropriate AWS and Databricks services.
• Assess existing ADF pipelines, triggers, dependencies, activities, parameters, transformations, and operational processes and determine suitable target patterns using AWS Glue, AWS Step Functions, AWS Lambda, Amazon Event Bridge, and/or Databricks Workflows, depending on workload characteristics.
• Lead the transition of the existing data lake from ADLS Gen2 to Amazon S3, including storage architecture, folder/object organization, partitioning, lifecycle management, access controls, encryption, and integration with Databricks.
• Provide technical leadership for Databricks on AWS, including migration/reconfiguration of existing Azure Databricks workloads, clusters/serverless compute, jobs, notebooks, Delta Lake datasets, storage access, secrets, IAM integration, networking, and governance.
• Own conceptual, logical, and physical data models aligned to business capabilities, enterprise standards, domain boundaries, canonical definitions, master/reference data, and target-state architecture.
• Lead SQL Server discovery, assessment, and migration planning across schemas, stored procedures, functions, triggers, jobs, data quality, security, and operational readiness.
• Define repeatable migration patterns for engine conversion, complex redesign, database consolidation, legacy retirement, schema conversion, data type mapping, incompatible SQL remediation, pilot execution, scaled portfolio delivery, and reusable tooling.
• Own data movement, change data capture, reconciliation, cutover, rollback, stabilization, post-migration validation, and production readiness across source and target systems.
• Define database engineering standards for infrastructure as code, schema-as-code, version control, migration scripts, release management, automated compliance checks, quality gates, and performance validation.
• Partner with application and platform teams to improve maintainability, including placement of business logic, indexing, query optimization, partitioning, connection management, workload isolation, and performance tuning.
• Lead, mentor, and coordinate cross-functional delivery while chairing design reviews, resolving technical issues, documenting key decisions, communicating risks and trade-offs, providing hands-on support for complex challenges, and building reusable standards, templates, accelerators, and knowledge-transfer materials.

Thanks & Regards

Rakesh Vangala

Team Lead

Burgeon IT Services LLC.

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