Senior Data Engineer (Hybrid- Jersey City ,NJ ) Face to face interview

Top 5 must haves: Senior Level

• Python
• Airflow/DBT
• Communication, both written & Verbal
• Kubernetes

Manager Notes: The role requires hands-on experience with DBT and Apache Airflow deployed on Kubernetes, specifically within an on-prem OpenShift environment.

If background is predominantly on Google Cloud Platform, and while this is valuable, we are currently more conservative with cloud-native platforms. This position involves closer interaction with infrastructure, including Kubernetes operations, Airflow design and implementation, and hands-on dbt model development in an on-prem setup.

Given these requirements, we are looking for someone with deeper, practical experience in DBT and Airflow within Kubernetes-based, on-prem environments.

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)