Senior Data Engineer - Hybrid

CyberCoders; Jersey City (NJ); Hybrid; USD 180,000 - 240,000; Full time

Job summary

CyberCoders is seeking a Senior Data Engineer for our AI/Healthcare team in Jersey City. This hybrid, full-time role focuses on building production data infrastructure to support high-volume applications and ML workflows.

You will own pipelines from ingestion to storage, design schemas in Snowflake and MySQL, deploy on AWS, and ensure data quality with monitoring and alerts. Collaboration with backend and ML engineers is essential.

Qualifications

• Design, build and optimize scalable data pipelines.
• Experience integrating external systems via APIs, webhooks, and CDC.
• Ensuring data quality, validation and transformation for analytics/ML.

Responsibilities

• Design, build, and maintain scalable, high-throughput data pipelines.
• Build integrations with external systems using APIs, webhooks, and CDC.
• Transform, validate, and normalize complex datasets for production and analytics.
• Design and optimize schemas across Snowflake and MySQL.
• Build data infrastructure supporting real-time applications and ML workloads.
• Deploy and operate production data pipelines and services in AWS.
• Implement monitoring, logging, alerting, and data-quality checks.
• Improve pipeline reliability, scalability, and performance.

Skills

Data pipelines

API integration

CDC

AWS

Data quality

Tools

Snowflake

MySQL

AWS

Job description

Senior Data Engineer | AI/Healthcare | $180K-$240K

Jersey City, NJ | Hybrid | Full-Time

We're working with a fast-growing technology company in the AI and healthcare space that's looking to add a Senior Data Engineer to its growing engineering team.

This is a hands-on role focused on building and scaling production data infrastructure that supports high-volume applications, analytics, and machine learning systems. You'll own critical pipelines from ingestion through transformation and storage while working closely with backend and ML engineers.

What You'll Do

• Design, build, and maintain scalable, high-throughput data pipelines
• Build integrations with external systems using APIs, webhooks, and change data capture (CDC)
• Transform, validate, and normalize complex datasets for production and analytical use
• Design and optimize schemas across Snowflake and MySQL
• Build data infrastructure supporting real-time applications and downstream ML workloads
• Deploy and operate production data pipelines and services in AWS
• Implement monitoring, logging, alerting, and data-quality checks
• Improve pipeline reliability, scalability, and performance