Senior Data Engineer
Share
Job Location:
Boston, NH - USA
Monthly Salary:
Not Disclosed
Posted on:
3 hours ago
Vacancies:
1 Vacancy
Job Summary
Role: Senior Data Engineer Airflow DBT Core Kubernetes/OpenShift
Location: Boston MA
Fulltime
Onsite
Job Summary
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
10 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
Expert-level Apache Airflow (DAG design scheduling performance tuning)
Expert-level dbt Core (data modeling testing macros implementation)
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
Cloud & Platform Experience
Experience running data platforms on cloud environments
Familiarity with containerized deployments CI/CD pipelines and Git-based workflows
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
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)
