FUSTIS LLC · 10 hours ago
Senior Data Engineer (Onsite Interview)
FUSTIS LLC is seeking a highly skilled Senior Data Engineer with extensive experience in enterprise data engineering. The role involves building, operating, and optimizing scalable data pipelines that support financial and accounting platforms, requiring expertise in Apache Airflow and dbt Core modeling.
Responsibilities
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
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
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
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
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
Qualification
Required
Python
Apache Airflow/DBT
Communication, both written & verbal
Kubernetes
OpenShift
8+ years of 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
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
Experience running data platforms on cloud environments
Familiarity with containerized deployments, CI/CD pipelines, and Git-based workflows
Preferred
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)