Full Stack JavaScript Developer (Mid Level Onsite)
Summary
Mid-level full stack JavaScript engineer supporting a high-visibility federal client onsite in Bethesda, MD, contributing across the full SDLC in an Agile team on enhancements, data integration, and modernization. Core stack: Angular, JavaScript/TypeScript, Node.js/Express, SQL/Elasticsearch/MongoDB, and Git.
About Futrend Technology, Inc.
Position Overview
- Experienced programmer with at least five years of application or systems development experience. Strong understanding of procedural and object-oriented programming and common design patterns. Demonstrated ability to work within large, complex codebases across the full technology stack. Capable of completing assignments independently with minimal supervision.
- Collaborative team player who works effectively with others and actively communicates to support shared goals and successful project delivery.
- A self-motivated learner committed to continuously expanding technical expertise and staying current with emerging technologies.
- Experience with web development technologies, including semantic HTML, CSS, JavaScript and TypeScript, DOM, Model/View/Controller (or similar), REST and JSON, and related server-side technologies, including NodeJS, ExpressJS and NPM. Extensive experience with the Angular framework is required.
- Familiarity with functional and event-driven programming concepts (callbacks, promises/futures, streaming, and reactive programming).
- Experience coding algorithms to process complex data structures, e.g., multi-level combinations of objects, lists and hash tables.
- Experience working with databases (SQL, Elasticsearch and MongoDB) and handling data through pipelines, ETL processes, and various file formats.
- Extensive experience with Git source code control, including advanced operations like rebasing and squashing.
- Ability to work with Linux environments and shell programming.
- Working knowledge of Python and pip, along with experience using numerical and data science libraries, including Keras and NumPy, to support machine learning implementation.
- Knowledge of AWS or comparable cloud platforms, including cloud-agnostic architectures and services.
- Knowledge of Medical Subject Headings or other medical terminologies.