Lead Aws Data Engineer - New York , Hybrid ( 12+ Years Only )

Level/Role: Lead Data Engineer
Location: Onsite NY/NJ based role

Position Overview:
We are seeking a highly skilled and experienced Lead AWS Data Engineer to join our team. This role requires deep
expertise in modern AWS cloud data engineering, with a focus on real-time streaming systems, large-scale data
processing, and wealth management domain knowledge. The ideal candidate will be a hands-on technologist with proven
leadership skills, able to architect, build, and optimize resilient data pipelines supporting mission-critical financial
systems.
Roles and Responsibilities:
Lead the design, development, and implementation of data streaming solutions leveraging Kafka, Kinesis, AWS
Glue, Lambda, and related AWS services.
Architect and manage data storage and processing solutions across S3, RDS (Postgres), Aurora, DynamoDB,
and Iceberg.
Implement robust monitoring and logging frameworks using Dynatrace and CloudWatch to ensure system
performance, reliability, and availability.
Define and enforce IAM policies and security best practices across AWS environments.
Oversee CI/CD pipelines and infrastructure as code using Terraform, Git strategy/branching, and Octopus
Deploy.
Partner with stakeholders to capture and translate business requirements into technical solutions, especially in
wealth management, trading (NSCC, BETA), and IBOR/TBOR platforms.
Deliver scalable, high-performance real-time data processing pipelines capable of handling large volumes of
financial market and client data.
Provide technical leadership and mentoring to junior engineers, fostering best practices in data engineering
and DevOps.
Required Skills & Experience
10+ years of professional experience in data engineering, with at least 5 years in AWS cloud environments.
Strong expertise in real-time data streaming technologies: Kafka, Kinesis, Glue, Lambda, SQS/SNS.
Hands-on experience with AWS storage & databases: S3, RDS (Postgres), Aurora, DynamoDB, Iceberg.
Proficiency in infrastructure as code (Terraform) and CI/CD (Git branching strategy, Octopus).
Strong background in monitoring & observability: Dynatrace, CloudWatch.
Excellent understanding of IAM policies, roles, and cloud security best practices.
Domain expertise in wealth management, trading data (NSCC, BETA), and IBOR/TBOR platforms.
Proven track record of working with large-scale, high-volume, real-time data pipelines.
Strong problem-solving skills and ability to design scalable, reliable, and efficient systems.
Preferred Qualifications:
Proven experience in the banking and financial services sector, with exposure to market research and trading
data ecosystems.
Background in wealth management, asset management, or banking financial domains strongly preferred.
Demonstrated leadership experience in managing and mentoring cross-functional engineering teams.