Data Engineer

Role Description

• 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.

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.

Requirements

• Full compensation packages are based on candidate experience.
• Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States.
• Remote - USA
• Salary range: $124,250 — $166,750 USD.

Benefits

• Health:
  • Medical/Dental/Vision
  • Premiums are 100% Company Paid
  • Health Savings Account
  • Life Insurance
  • Disability Insurance
• Financial:
  • 401k Retirement Plan
  • Company Stock Options
  • Home Office Budget
• Leave:
  • Flexible Time Off (FTO) plus all Federal Holidays, one week for Thanksgiving, and two weeks for Christmas and New Year’s.
  • Paid Parental Leave.
• Learning:
  • Reimbursement for approved trainings/subscriptions.
  • Conferences (travel, lodging, and fees).