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Full Stack Engineer – Data & Analytics-W2 -Any visa

HUMAC INC.Phoenix, AZ🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationPhoenix, AZ, United States
SQLEncryptionAngularBigQueryPhoenixReactKubernetesCI/CD

Job description

Job Title: Full Stack Engineer – Data & Analytics-w2 -Any Visa

Location: Phoenix, AZ-Locals

Position Summary

We are seeking an experienced Full Stack Engineer to design, develop, and support enterprise-scale data platforms and APIs. The ideal candidate will have strong backend development skills, modern frontend experience, cloud-native architecture, data integration, and API management expertise.

Key Responsibilities

  • Design and develop enterprise-grade APIs, event-driven integrations, and data services.

  • Build and maintain cloud-native applications deployed on Kubernetes.

  • Develop modern web applications using React (preferred) and/or Angular.

  • Implement secure data exchange using encryption, authentication, and authorization.

  • Develop enterprise integrations using APIs, file-based exchanges, and cloud data platforms.

  • Work with data engineering teams to support large-scale enterprise datasets.

  • Lead technical design reviews and architecture discussions.

  • Troubleshoot production issues and optimize application performance.

  • Implement CI/CD pipelines and DevSecOps best practices.

  • Mentor engineers and establish development standards.

  • Support consumer onboarding to enterprise APIs and data products.

Required Skills – Data Engineering & Analytics

  • Experience working with large-scale datasets.

  • Strong SQL skills.

  • Hands-on experience with Google BigQuery.

  • Knowledge of Data Lake architectures.

  • Experience with data ingestion frameworks.

  • Experience developing and supporting data transformation pipelines.

Technical Requirements

  • Backend: Enterprise API development and event-driven architecture.

  • Frontend: React (preferred) or Angular.

  • Cloud & Containers: Cloud-native applications and Kubernetes.

  • Data & Analytics: SQL, BigQuery, Data Lakes, Data Ingestion, and Data Transformation.

  • DevOps: CI/CD and DevSecOps practices.

  • Security: Encryption, authentication, and authorization.

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