Senior Software Engineer

Entarian provides mission-critical engineering and technology solutions for defense and civilian missions. The Senior Software Engineer will support the full software development lifecycle for a CNMOC data dissemination project, including architecture, coding, testing, cloud and data pipeline operations, and maintenance. The role also involves translating customer needs into user stories, mentoring developers, facilitating Agile ceremonies, and communicating technical solutions.

Responsibilities:

• You will participate in all aspects of the software development lifecycle of a mission critical product including scope and work estimation, architecture and design, coding and unit testing
• Support all aspects of software development (designing, coding, testing, debugging, and maintaining products)
• Translate customer needs into user stories and deliver working capabilities at the conclusion of each sprint
• Mentor other software developers on product team to enhance their skills
• Participate and/or lead sprint demonstrations and facilitate implementation of agreed upon ideas identified at retrospectives
• Work with others on product teams to develop solutions to hard problems that are impeding progress
• Effectively communicate technical challenges, options considered, and the recommended solution to team leads

Requirements:

• • Education & Experience: Bachelor's degree (Computer Science, Software Engineering, Data Engineering/Data Science, or related) with 6+ years of relevant experience
• • Clearance: Active Secret
• Directive 8570.1/8140 – IAT II: CompTIA Security+ (or ability to obtain within onboarding window)
• • Programming & Data: Strong Python background with modern data processing libraries (Polars, Pandas, Pydantic); fluency with JSON/XML formats and supporting libraries
• • Pipelines & Operations: Proven experience designing/maintaining ETL/ELT pipelines for structured and unstructured datasets in operational environments; mastery of data engineering concepts (velocity, volume, variety, veracity)
• • Version Control & TDD: Structured programming with Git/Subversion; experience with test‑driven development and Agile lifecycle tools (Jira, Jenkins, JUnit, GitLab)
• • Databases & Modeling: Strong understanding of data modeling, data integration, and database design; hands-on with PostgreSQL/PostGIS, SQL Server, or Oracle
• • Cloud & Containers: Practical experience with AWS and container technologies; familiarity with DevSecOps frameworks
• • Geospatial & APIs: Experience integrating geospatial systems and enterprise data platforms/APIs (e.g., ESRI stack, ERDDAP)
• • Communication: Excellent written and verbal communication skills; ability to self-start and work independently with minimal supervision
• • Advanced Pipeline Ops: Experience designing, developing, and maintaining large-scale ingestion, transformation, and analytics workflows; strong background in data orchestration and automation tools
• • Data Governance: Applied knowledge of governance policies, metadata/lineage, cataloging (e.g., DataHub/Amundsen), and compliance reporting
• • Streaming & Event Data: Experience with streaming platforms (e.g., Kafka, Kinesis) and time-series data stores; optimization for multi-parameter time-based series, preferably in Meteorology/Oceanography domains
• • AI/ML Enablement: Experience applying AI to accelerate data processing and analytics workflows
• • Geospatial Tooling: Proficiency with ESRI tools and broader ESRI ecosystem
• • Security & Compliance: Hands-on with Cybersecurity best practices and DISA STIG checklists; familiarity with DevSecOps pipelines
• • Cloud & Containers (Advanced): Experience with container runtimes (e.g., OpenShift, Kubernetes, Podman); IaC (Terraform/CloudFormation); cost/performance optimization in AWS
• • Domain Tooling: Experience with IRODS; exposure to Spring MVC, Java/Java Servlet, C++, and front-end (JavaScript, HTML, CSS, TypeScript) for end‑to‑end data application integration
• • Test Automation: Familiarity with Selenium/Citrus for automated validation in data-adjacent services
• • Customer Engagement: Demonstrated history of direct customer support and structured escalation