обновлено 13 дней назад
Software Engineer and Analytical Support (Fullstack)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer and Analytical Support (Python/React/TypeScript): Building custom tools, scripts, and analytics that parse, normalize, and make large-scale datasets queryable for analyst teams with an accent on rapid iteration, customer collaboration, and data-focused problem solving. Focus on integrating database and frontend capabilities, developing tactical solutions, and supporting complex analytical workflows.
Location: Requires Top Secret/SCI clearance with Full Scope Poly.
Company
develops custom software tools and analytical solutions for teams working across varied problem sets.
What you will do
- Work with analysts and team members to understand user needs and deliver practical solutions.
- Build custom tools, scripts, and analytics to parse and normalize data.
- Develop fast-turnaround solutions and iterate frequently with customers.
- Use and extend existing corporate tools, platforms, and team capabilities.
- Identify opportunities to broaden tools across multiple efforts and support shared functionality.
- Collaborate with analysts, data scientists, software engineers, and customer organizations.
Requirements
- Top Secret/SCI clearance with Full Scope Poly is required.
- 12 years of professional experience, or a bachelor’s degree in a technical discipline plus 8 years of experience.
- Experience with datastores and databases such as SQL and Elastic.
- Ability to write scripts, preferably in Python.
- Experience interacting with customers.
- Experience with frontend JavaScript development using React and TypeScript, plus familiarity with Git, Confluence, and Linux.
Nice to have
- Experience with big data, MapReduce, large-scale analytics, or machine learning.
- DevOps or Docker experience.
- Knowledge of network analysis, including network mapping, packet analysis, or network topology.
Culture & Benefits
- Work closely with users and customer teams to understand problems and improve tools.
- Emphasis on speed, efficiency, accuracy, creativity, and short feedback loops.
- Peer collaboration across software engineering, analytics, data science, and customer support functions.
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