Description

Lead the design and execution of large-scale data modernization initiatives, focusing on migrating ETL processes from legacy systems to modern data 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.
• Provide technical leadership and mentorship to data engineers, ETL developers, and cross-functional teams.
• Develop automation strategies to streamline data workflows, deployment, and monitoring while ensuring data quality and compliance.

Required Skills

• 8+ years of experience in data architecture, data engineering, or related roles.
• Strong expertise in database systems (relational and/or NoSQL) and data modeling.
• 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.
• Experience designing and implementing data architecture frameworks and standards.

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