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    Dysrupit

    Data Engineering

    Full Stack Java Engineer

    Makati City, PhilippinesOn-SiteFull-time4–6 yrs experiencePosted 1mo ago
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    Job description

    Experience & Competencies:

    • 4–6 years of experience in Software Development
    • Strong foundation in software engineering principles, data structures, and design patterns
    • Experience developing scalable web and distributed systems
    • Strong understanding of Agile and DevOps practices
    • Exposure to cloud-native development and modern engineering practices
    • Ability to contribute to end-to-end delivery (design, development, testing, deployment)
    • Strong problem-solving mindset with ability to learn new technologies quickly
    • Effective communication skills across technical and business stakeholders
    • Interest or experience in data engineering, Python, or AI capabilities

    Technical Skills:

    Backend & Core Engineering

    • Experience in Java (preferably Java 11 or above)
    • Experience with Spring Boot and REST API development
    • Basic understanding of microservices architecture
    • Experience with SQL and relational databases (MSSQL/PostgreSQL)
    • Familiarity with event-driven systems (e.g., Kafka, MQ) is a plus

    Frontend / Full Stack

    • Experience with JavaScript frameworks (React or Angular)
    • Understanding of HTML, CSS, and modern UI development practices
    • Ability to integrate frontend applications with backend APIs

    Python & AI Exposure

    • Working knowledge of Python for scripting, data processing, or backend services
    • Familiarity with libraries such as Pandas, NumPy, or FastAPI/Flask
    • Exposure to AI/ML concepts or tools (e.g., basic model usage, APIs, automation use cases)
    • Understanding of working with structured/unstructured data (JSON, text, logs)

    Job details are sourced from the employer's original posting.

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    About the company

    Dysrupit

    Dysrupit designs data products and data pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost effective. They utilize software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.

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    Industry
    Data Engineering
    Open roles
    12

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