Job Summary
We are seeking a highly skilled Senior Data Engineer with 10+ years of professional experience in enterprise data engineering, including hands-on expertise in Apache Airflow DAG development, dbt Core modeling and implementation, and cloud-native container platforms such as Kubernetes and OpenShift. This role is responsible for building, operating, and optimizing scalable data pipelines supporting financial and accounting platforms, enterprise system migrations, and high-volume data processing workloads. The position requires strong practical experience with dbt and Airflow deployed on Kubernetes, specifically within an on-premises OpenShift environment, along with close collaboration with infrastructure teams on Kubernetes operations, Airflow implementation, data modeling, performance tuning, and distributed workload management.

Key Responsibilities
• Design, develop, operate, and optimize enterprise-scale data platforms in production environments.
• Develop and maintain Apache Airflow DAGs, including scheduling, orchestration, monitoring, and performance tuning.
• Design and implement dbt Core models, including data transformations, testing, macros, and reusable components.
• Deploy and support Apache Airflow and dbt workloads on Kubernetes-based, on-premises OpenShift environments.
• Work closely with infrastructure teams on Kubernetes operations and containerized data platform deployments.
• Build and optimize scalable data pipelines for financial and accounting platforms.
• Support enterprise system migrations and high-volume data processing workloads.
• Develop automation and data engineering solutions using Python.
• Perform complex data transformations and analytics using SQL.
• Manage distributed workloads and optimize platform and pipeline performance.
• Support cloud-based data platforms and containerized deployments.
• Work with CI/CD pipelines and Git-based development workflows.
• Troubleshoot production data platform issues and implement sustainable solutions.

Required 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 experience with Apache Airflow, including DAG design, scheduling, orchestration, and performance tuning.
• Expert-level experience with dbt Core, including data modeling, testing, macros, and implementation.
• Hands-on experience deploying and operating Airflow and dbt on Kubernetes, specifically within an on-premises OpenShift environment.
• 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 working with containerized deployments, CI/CD pipelines, and Git-based workflows.
• Experience running and supporting data platforms in cloud environments.

Preferred Qualifications
• Experience supporting financial services or accounting platforms.
• Experience with enterprise system migrations, including migration from legacy platforms to modern data stacks.
• Experience working with Oracle or other enterprise data warehouses.