Description

Lead the architecture and execution of large-scale data modernization, migrating ETL processes from legacy systems to modern platforms.

This role is hybrid.

Responsibilities

• Lead end-to-end architecture and execution of ETL migration from legacy systems to cloud-based or next-generation data ecosystems.
• Define and enforce architectural standards, frameworks, and best practices for data engineering and integration.
• Design scalable, high-performance data pipelines and workflows to support enterprise-level data processing.
• Evaluate and implement next-generation ETL and data integration technologies, including automation strategies for workflows and monitoring.
• Provide technical leadership and mentorship to data engineers and cross-functional teams while ensuring data quality, governance, and security.

Required Skills

• 8+ years of experience in data architecture, data engineering, or related roles.
• Strong expertise in database systems, including relational and NoSQL databases, with proven data modeling skills.
• Proven experience with ETL design, development, and migration from legacy systems.
• Hands-on experience with modern ETL/data integration tools and cloud-native pipelines.
• Deep understanding of large-scale data processing and performance optimization.
• Strong knowledge of automation, orchestration, and CI/CD practices in data environments.
• Ability to lead technical decision-making and translate business requirements into robust data architecture solutions.

Preferred Skills

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with data lake, data warehouse, and lakehouse architectures.
• Experience with streaming data technologies and real-time processing.

Key Skills

Education

Any Graduate