5+ years of experience in building and maintaining production data pipelines and databases on Kubernetes.
Proficient in designing and operating Kafka/Redpanda data streaming solutions.
Experience with containerization technologies like Docker and orchestration systems such as Kubernetes.
Knowledge of systems engineering principles for data layer reliability and scalability.
Familiarity with API and container security, as well as AWS Cloud Security best practices.
Strong problem-solving skills and ability to work both independently and collaboratively.
Excellent communication skills for conveying complex ideas to diverse audiences.
Responsibilities
Design data workflows and pipelines for ETL/ELT, ensuring data quality and secure information exchange.
Implement systems engineering principles for reliable and maintainable data layer systems, including backup strategies.
Architect and operate data streaming technologies on Kubernetes, focusing on reducing operational complexity.
Collaborate with platform teams to establish best practices for configuration management and performance optimization.
Automate infrastructure provisioning and monitoring using Terraform, integrating cybersecurity best practices.
Ensure compliance of data layer systems with industry and DoD regulations and standards.
Stay updated on industry trends in Kubernetes, containerization, and data engineering.
Benefits
Opportunity to work on high-impact projects for the U.S. government.
Dynamic work environment with evolving responsibilities.
Collaboration with a skilled platform team.
Exposure to cutting-edge technologies in data engineering and cloud environments.
Travel opportunities for professional development and networking.
Full Job Description
EMPLOYER IS A CONTRACTOR FOR THE U.S. GOVERNMENT. THIS POSITION WILL REQUIRE U.S. CITIZENSHIP. Responsibilities:
Designing data workflows, pipelines, and pathways to support ETL/ELT, while ensuring data-quality and exchange of sensitive information across AWS cloud and on-prem environments.
Implementing systems engineering principles to ensure the reliability, scalability, and maintainability of data layer systems, including backup and recovery strategies
Architecting, deploying, and operating data streaming technologies (Kafka, Redpanda, Kinesis, etc ) on Kubernetes with an emphasis on declarative definitions to reduce complexity in day-2 operations
Working with a platform team to implement best practices for configuration management, security, and performance optimization within Kubernetes and AWS environments
Working with a platform team to automate infrastructure provisioning, monitoring, and scaling using tools such as Terraform working with cybersecurity SMEs to incorporate best practices and techniques to defend our data layer against potential threats
Ensuring that our data layer systems are compliant with industry and DoD regulations, standards, and best-practices
Staying up-to-date with industry trends and emerging technologies related to Kubernetes, containerization, and data engineering
Travel Expectations/Requirements: 6-10 times per year
The listed responsibilities are not exhaustive and additional responsibilities may be assigned based on the evolving needs of the organization. We are seeking a dynamic individual who is able to adapt and take on new responsibilities as they arise.
*Preferred Experience and Qualifications:
Demonstrated experience (minimum 5 years) in building and maintaining production data pipelines, databases, and data exchange services on Kubernetes Experience in designing, deploying, and operating Kafka / Redpanda data streaming solutions on Kubernetes
Experience in creating data pipelines from scratch with the ability to process data in large volumes and manage data stores
Experience with containerization technologies such as Docker and container orchestration systems like Kubernetes
Knowledge of systems engineering principles to ensure the reliability, scalability, and maintainability of data layer systems Familiarity with API Security, Container Security, AWS Cloud Security Familiarity with cybersecurity principles and best practices for securing data layer systems
Excellent problem-solving skills, with the ability to work independently and as part of a team
Excellent communication skills, with the ability to convey complex ideas to both technical and non-technical team members
The selected candidate will be subject to a pre-employment background check ("CBI") and must be able to obtain and maintain a Secret-level DoD security clearance
Experience with machine learning and generative AI models
