Data Platform Engineer

Data Platform Engineer

Location: Jersey City, NJ

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

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
• 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
• Cloud & Platform Experience
• 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)