Senior Data Engineer

Seaglass Technology Partners, LLC; Jersey City (NJ); On-site; USD 140,000 - 220,000; Full time

Job summary

Seaglass Technology Partners, LLC is seeking a Senior Data Engineer with 8+ years of enterprise data experience to build and optimize scalable data pipelines in production. You will work on financial and accounting platforms, migrations, and high-volume workloads.

The role emphasizes workflow orchestration with Airflow and dbt Core, mastery of Kubernetes/OpenShift, SQL, and cloud deployments. You will contribute to performance tuning and distributed workload management inside containerized

Qualifications

• 8+ years of professional data engineering, analytics engineering, or platform engineering experience.
• Proven ability to design and support enterprise-scale data platforms in production environments.
• Strong Python proficiency for data engineering and automation.
• Experience with cloud-native deployments and container orchestration (Kubernetes/OpenShift).

Responsibilities

• Build, operate, and optimize scalable data pipelines for financial and accounting workloads.
• Design and implement workflow orchestration using Airflow and dbt Core.
• Tune performance and manage distributed workloads in containerized environments.
• Collaborate with stakeholders on migrations from legacy systems to modern data stacks.

Skills

Python

Kubernetes/OpenShift

Distributed workload management

SQL

Cloud environments

CI/CD Git workflows

Job description

We are seeking a highly skilled Senior Data Engineer with 8+ years of hands-on experience in enterprise data engineering, including deep expertise in Apache Airflow DAG development, dbt Core modeling and implementation, and cloud-native container platforms (Kubernetes / OpenShift).

This role is critical to building, operating, and optimizing scalable data pipelines that support financial and accounting platforms, including enterprise system migrations and high-volume data processing workloads.

The ideal candidate will have extensive hands-on experience in workflow orchestration, data modeling, performance tuning, and distributed workload management in containerized environments.

Required Skills & Qualifications:

Experience

• 8+ years of professional experience in data engineering, analytics engineering, or platform engineering roles
• Proven experience designing and supporting enterprise-scale data platforms in production environments

Must-Have Technical Skills

• Strong proficiency in Python for data engineering and automation
• Deep understanding of Kubernetes and/or OpenShift in production environments
• Extensive experience with distributed workload management and performance optimization
• Strong SQL skills for complex transformations and analytics
• Experience running data platforms on cloud environments
• Familiarity with containerized deployments, CI/CD pipelines, and Git-based workflows

Preferred Qualifications

• Experience supporting financial services or accounting platforms
• Exposure to enterprise system migrations (e.g., legacy platform to modern data stack)
• Experience with data warehouses (Oracle)