Overview
Skills
Job Details
Data Engineering Lead
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.
- Bachelor's degree in computer science, Engineering, or related field; advanced degree a plus.
- Extensive expertise in data engineering, with a strong emphasis on real-time streaming technologies.
- Excellent problem-solving, analytical, and communication skills, with the ability to engage effectively with both technical and business stakeholders.
- Collaborative mindset with a track record of driving successful outcomes in team environments.
CST provides its clients with complete, cost-effective, end-to-end personnel solutions across a range of industrial domains. CST's mission is to empower businesses around the world to make better, faster operational decisions.