Data Engineer
Jersey City, New Jersey, United States of America
Contract
3 hours ago
$55 USD
Key skills
PythonSQLData EngineeringAnalyticsAirflowApache AirflowdbtKubernetesOpenShiftGitPerformance OptimizationCI/CDCollaboration
About this role
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
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
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
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
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
Support financial reporting, accounting, and regulatory data use cases
Enforce data engineering standards, security best practices, and governance policies
Required Skills & Qualifications:
Experience
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
Proven experience designing and supporting enterprise-scale data platforms in production environments
Must-Have Technical Skills
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
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
Familiarity with containerized deployments, CI/CD pipelines, and Git-based workflows