Data Platform Engineer

Jersey, NJ - USA

Monthly Salary: Not Disclosed

Posted on: 18 hours ago

Vacancies: 1 Vacancy

Job Summary

Location: Onsite 3 days/week in Jersey City NJ no relocation

Start: ASAP
Interview Process: 2 rounds 1 virtual and 1 in person

*When submitting please make sure resume is 3 pages or less this is required by BBH; also please include their LinkedIn profile with picture and full name *

Must have:
-Apache Airflow/DBT
-Kubernetes
-OpenShift

-Python

-Communication both written & verbal
-8 years of experience

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.

Key Responsibilities:

Data Pipeline & Orchestration

Design develop and maintain complex Airflow DAGs for batch and event-driven data pipelines
Implement best practices for DAG performance dependency management retries SLA monitoring and alerting
Optimize Airflow scheduler executor and worker configurations for high-concurrency workloads

dbt Core & Data Modeling

Lead dbt Core implementation including project structure environments and CI/CD integration
Design and maintain robust dbt models (staging intermediate marts) following analytics engineering best practices
Implement dbt tests documentation macros and incremental models to ensure data quality and performance
Optimize dbt query performance for large-scale datasets and downstream reporting needs

Cloud Kubernetes & OpenShift

Deploy and manage data workloads on Kubernetes / OpenShift platforms
Design strategies for workload distribution horizontal scaling and resource optimization
Configure CPU/memory requests and limits autoscaling and pod scheduling for data workloads
Troubleshoot container-level performance issues and resource contention

Performance & Reliability

Monitor and tune end-to-end pipeline performance across Airflow dbt and data platforms
Identify bottlenecks in query execution orchestration and infrastructure
Implement observability solutions (logs metrics alerts) for proactive issue detection
Ensure high availability fault tolerance and resiliency of data pipelines

Collaboration & Governance

Work closely with data architects platform engineers and business stakeholders
Support financial reporting accounting and regulatory data use cases
Enforce data engineering standards security best practices and governance policies

Location: Onsite 3 days/week in Jersey City NJ no relocation Start: ASAP Interview Process: 2 rounds 1 virtual and 1 in person *When submitting please make sure resume is 3 pages or less this is required by BBH; also please include their LinkedIn profile with picture and full name * Must have:...