Manager

We are seeking a Data Migration Engineer to oversee the planning, execution, and validation of our enterprise data migration strategies. In this role, you will be responsible for moving critical data from legacy environments to modern, scalable cloud-based target architectures. You will design robust ETL pipelines, bridge gaps between mismatched schemas, and ensure security, integrity, and absolute accuracy of data throughout the transition. You will focus on designing high-throughput, parallel loading frameworks to move massive datasets efficiently from legacy systems to the cloud. As a core member of our data engineering team, you will utilize the AWS data ecosystem to build secure, fault-tolerant pipelines that maximize data velocity while ensuring absolute data integrity

• AWS Pipeline Development: Build production-grade data pipelines using native AWS services like Glue, EMR, Athena, and Lambda.
• Cloud Warehousing: Practical experience loading and optimizing target architecture in Amazon Redshift on AWS.
• Data Lake Integration: Extract and transform structured, semi-structured, and unstructured legacy data into optimized cloud storage formats (e.g., Parquet, ORC) on Amazon S3.

Required Skills & Qualifications

AWS & Cloud Engineering

• Core AWS Data Stack: Advanced, hands-on experience with AWS Glue (ETL/Catalog), Amazon S3, AWS Lambda, and Amazon Athena.
• Big Data Compute: Strong proficiency using Amazon EMR or managed Apache Spark / PySpark environments to orchestrate distributed data processing.
• Database: Good experience in Amazon Redshift.

Professional Attributes

• System Scale Mindset: Ability to identify and resolve concurrency bottlenecks, deadlock scenarios, and network throttling limits.

Experience & Education

• Experience: 5+ years of data engineering experience, with at least 2 years dedicated to building high-volume parallel data pipelines or migrating legacy workloads to AWS.
• Education: Bachelor’s degree in computer science, Software Engineering, or a closely related technical field.

Certification (Preferred): AWS Certified Data Engineer – Associate/Professional or AWS Certified Solutions Architect

Experience & Education

• Experience: 5+ years of data engineering experience, with at least 2 years dedicated to building high-volume parallel data pipelines or migrating legacy workloads to AWS.
• Education: Bachelor’s degree in computer science, Software Engineering, or a closely related technical field.
• Certification (Preferred): AWS Certified Data Engineer – Associate/Professional or AWS Certified Solutions Architect.