AWS Data Engineer

Job Overview

NTT DATA's Client is seeking an AWS Data Engineer to design, develop, and maintain scalable cloud-based data pipelines using AWS services such as Glue, EMR, S3, RDS, Data Sync, and DMS.

• Build and optimize batch and streaming data orchestration workflows to support enterprise data platforms.
• Lead large‑scale data migration efforts, including legacy‑to‑cloud transformations and replication strategies.
• Perform data modeling, transformation, and reconciliation to ensure high‑quality, consistent datasets across systems.
• Implement secure data access patterns following least‑privilege principles for pipelines and datasets.
• Collaborate with data architects, analysts, and business stakeholders to understand data requirements and deliver solutions.
• Establish robust data validation, reconciliation, and audit mechanisms to meet regulatory and reporting requirements.
• Troubleshoot and optimize performance of ETL/ELT pipelines and data workflows in AWS environments.
• Support governance, compliance, and audit readiness for data platforms in regulated environments (finance/reporting).

• 5+ years of experience in data engineering, with strong hands‑on expertise in AWS data services (Glue, EMR, S3, RDS, Data Sync, DMS).
• 5+ years of proven experience building and managing data pipelines (batch and streaming) in cloud environments.
• 5+ years of strong experience in data migration, transformation frameworks, and large‑scale data replication.
• 5+ years of deep understanding of data modeling, data transformation, and reconciliation techniques.
• 5+ years of experience designing and implementing secure data access and governance (least privilege principles).
• 5+ years of hands‑on experience with data validation, auditing, and reconciliation processes.
• Familiarity with regulatory or finance data environments and reporting workloads.
• 5+ years of strong problem‑solving skills and ability to work in a collaborative, fast‑paced environment.

• Experience with real‑time/streaming technologies such as Kafka or Kinesis.
• Exposure to data warehousing platforms such as Redshift or Snowflake.
• Experience with infrastructure‑as‑code tools (Terraform, Cloud Formation).
• Knowledge of Dev Ops practices and CI/CD for data pipelines.
• Prior experience working in regulated industries (Financial Services, Healthcare, etc.).

Minimal travel required (