Sr WAM-AWS-Data-Engineer

Job Summary

We are seeking a highly skilled Senior AWS Data Engineer to design, develop, and support modern cloud-based data platforms on Amazon Web Services (AWS). The ideal candidate will have strong expertise in AWS data engineering technologies, Python/PySpark development, workflow orchestration, and data lake architectures, along with experience delivering scalable enterprise-grade data solutions.

The role involves building and maintaining data ingestion, transformation, and analytics pipelines supporting financial services applications, advisor platforms, reporting systems, and enterprise data initiatives. Candidates with prior experience in Wealth Asset Management (WAM) domains will be highly preferred.

Role: AWS Data Engineer Senior

Experience: 5-8 years

Domain: Wealth Management, Asset Management, Capital Markets, Investment Banking, Financial

Key Responsibilities

AWS Data Engineering Development

• Design, develop, and maintain scalable data pipelines using AWS Glue (PySpark), Amazon S3, AWS Step Functions, and Athena.
• Build robust ETL/ELT solutions for batch and near real-time data processing.
• Develop reusable PySpark frameworks and data transformation components.
• Work closely with architects and business stakeholders to implement data platform requirements.
• Participate in migration and modernization initiatives from on-premises data platforms to AWS cloud environments.

Data Lake Data Architecture

• Implement and support enterprise data lakes using Medallion Architecture (Bronze, Silver, Gold).
• Develop and maintain Apache Iceberg tables for efficient storage, schema evolution, and incremental processing.
• Ensure data quality, lineage, reconciliation, and auditability across the data platform.
• Contribute to data modeling and optimization efforts for analytical workloads.

Workflow Orchestration Automation

• Develop and maintain Apache Airflow (MWAA) workflows and DAGs.
• Automate data movement, validation, monitoring, and notification processes.
• Implement retry mechanisms, dependency management, and failure handling within workflows.
• Integrate Airflow with AWS Glue, S3, Athena, and downstream applications.

AWS Cloud, Security Infrastructure

• Implement AWS security best practices, including IAM roles, KMS encryption, and secrets management.
• Support infrastructure provisioning and deployment activities using Terraform.
• Collaborate with DevOps, infrastructure, and security teams to maintain secure and reliable cloud environments.
• Assist in configuring VPC endpoints, networking connectivity, and service integrations.

Production Support Operational Excellence

• Monitor and troubleshoot production data pipelines and workflows.
• Perform performance tuning of AWS Glue jobs and Spark workloads.
• Implement logging, monitoring, and alerting using Amazon CloudWatch.
• Participate in incident resolution, root cause analysis, and continuous improvement initiatives.
• Ensure adherence to enterprise operational and governance standards.

Collaboration Continuous Improvement

• Collaborate with cross-functional teams, including data architects, analysts, application teams, and business users.
• Participate in code reviews, design discussions, and technical documentation.
• Mentor junior engineers and share AWS data engineering best practices.
• Stay current with emerging AWS services and modern data engineering trends.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.