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Design, develop, and maintain scalable cloud-based data pipelines using AWS services such as Glue, EMR, S3, RDS, DataSync, 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).
Job Responsibility
Design, develop, and maintain scalable cloud-based data pipelines using AWS services such as Glue, EMR, S3, RDS, DataSync, 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)
Requirements
5+ years of experience in data engineering, with strong hands-on expertise in AWS data services (Glue, EMR, S3, RDS, DataSync, 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
AWS data services
data pipelines
data migration
data modeling
data validation
data governance
Nice to have
Experience with real-time/streaming technologies (e.g., Kafka, Kinesis)
Exposure to data warehousing platforms (Redshift, Snowflake, etc.)
Experience with infrastructure-as-code (Terraform, CloudFormation)
Knowledge of DevOps practices and CI/CD for data pipelines
Prior experience working in regulated industries (Financial Services, Healthcare, etc.)