Forward Deployed Data Engineer (TS/SCI)

Skills

About the Role

You will partner directly with customers to design and deploy secure, scalable cloud-based data lakehouse solutions on AWS. You will own and deliver production-ready ETL/ELT pipelines using Python, Apache Airflow, Spark, and SQL optimized for petabyte-scale workloads. You will containerize and deploy services on Kubernetes (EKS), manage infrastructure as code with Terraform or CloudFormation, and design integrations that ingest data from message buses, APIs, and relational databases. You will implement observability (Prometheus, Datadog, NewRelic), uphold SLAs, and support mission-critical production systems—resolving incidents alongside customer operations teams. You should be prepared to travel to client sites as needed and must possess an active TS/SCI clearance.

Requirements

• Bachelor's degree or equivalent in Computer Science, Engineering, or related field
• 4+ years of hands-on experience building and deploying data pipelines in Python
• Proven expertise with Apache Airflow including DAG development and scheduler tuning
• Strong knowledge of Apache Spark including Spark SQL, DataFrames, and performance tuning
• Deep SQL skills with experience optimizing queries using window functions and CTEs
• Professional experience deploying cloud-native architectures on AWS including S3, EMR, EKS, IAM, and Redshift
• Familiarity with secure cloud environments and implementing FedRAMP or FISMA controls
• Experience deploying applications and data workflows on Kubernetes (preferably EKS)
• Infrastructure-as-Code proficiency with Terraform or CloudFormation
• Experience with GitOps and CI/CD using Jenkins, GitLab CI, or similar tools
• Excellent verbal and written communication skills
• Willingness and ability to travel up to 25%
• Active TS/SCI clearance (Polygraph strongly preferred)

Responsibilities

• Partner with customers to design and deploy secure scalable cloud-based data lakehouse solutions on AWS
• Build and deliver production-ready ETL/ELT pipelines using Python, Apache Airflow, Spark, and SQL
• Containerize and deploy services on Kubernetes (EKS) and manage infrastructure with Terraform or CloudFormation
• Design data integrations ingesting from message buses, APIs, and relational databases and embed real-time analytics
• Participate in all phases of the software development lifecycle including requirements, architecture, implementation, testing, and secure deployment
• Implement observability solutions and uphold SLAs
• Support production systems and resolve incidents with customer operations teams
• Conduct knowledge sharing and maintain up-to-date documentation
• Travel up to 25% to client sites as needed

Benefits

• Eligibility to participate in TRM's equity plan