Senior Data Tech Lead/Architect
- Provide technical solution discovery effort on any new capabilities or new functionality.
- Assist PO with technical user stories to ensure healthy backlog features
- Lead the development of real-time data pipelines using AWS DMS, MSK, Kafka or Glue Streaming and for CDC ingestion from multiple SQL Server sources (RDS/on-prem).
- Build and optimize streaming and batch data pipelines using AWS Glue (PySpark) to validate, transform, and normalize data to Iceberg and DynamoDB.
- Define and enforce data quality, lineage, and reconciliation logic with support for both streaming and batch use cases.
- Integrate with S3 Bronze/Silver layers and implement efficient schema evolution and partitioning strategies using Iceberg.
- Collaborate with architects, analysts, and downstream application teams to design API and file-based egress layers.
- Implement monitoring, logging, and event-based alerting using CloudWatch, SNS, and EventBridge.
- Mentor junior developers and enforce best practices for modular, secure, and scalable data pipeline development.
- 6+ years of hands-on expert level data engineering experience in cloud-based environments (AWS preferred) with event driven implementation
- Strong experience with Apache Kafka / AWS MSK including topic design, partitioning, and Kafka Connect/Debezium
- Proficiency in AWS Glue (PySpark) and for both batch and streaming ETL
- Working knowledge of AWS DMS, S3, Lake Formation, DynamoDB, and Iceberg
- Solid grasp of schema evolution, CDC patterns, and data reconciliation frameworks
- Experience with infrastructure-as-code (CDK/Terraform) and DevOps practices (CI/CD, Git)
- Familiarity with PostgreSQL, Athena, Step Functions, and Lambda
- Knowledge of event-driven architectures and microservices-based data APIs (This should be the required skills)
- Familiar with data lake concept
- Familiar with Financial or Financial Wealth management data domain
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