ReactJS with Azure developer

Reactjs With Azure Developer

Reactjs with Azure (majority work), Python, Airflow, Spark with Kubernetes. And ETL Data knowledge. The ideal candidate is a Reactjs frontend engineer with Azure cloud deployment expertise who can also design and orchestrate data workflows in Airflow, perform Python scripting and run Spark jobs on Kubernetes. They should be comfortable with Helm, Docker, and CI/CD pipelines for both application and data workloads. In addition to frontend work, the candidate will collaborate with Data Engineering team to deploy and orchestrate workflows in Apache Airflow and run Spark jobs on Kubernetes for large-scale data processing.
This is a cross-functional role — 70% frontend & Azure deployment, 30% data workflow orchestration and Kubernetes-based big data processing.
Candidate Profile – Reactjs + Azure (primary), Airflow, Spark on Kubernetes
1. Core Frontend Expertise (primary)
Reactjs (3+ years) — building scalable, component-based SPAs.
Strong in JavaScript (ES6+) and TypeScript.
Experience with state management (Redux, Zustand, or Recoil).
UI frameworks: Material-UI, Ant Design, or TailwindCSS.
REST API and GraphQL integration.
Performance optimization (lazy loading, memoization, code splitting).
Unit testing with Jest, React Testing Library, or Cypress.
2. Azure Cloud Skills (majority work)
Azure App Services and Azure Static Web Apps for frontend hosting.
Azure Kubernetes Service (AKS) — deploying containerized apps.
Azure Container Registry (ACR) — building and pushing Docker images.
Azure Key Vault — secure secrets management.
Azure DevOps Pipelines — CI/CD for React apps.
Familiarity with Helm charts for AKS deployments.
Azure Storage (Blob, Table) for static assets and logs.
3. Airflow (Workflow Orchestration)
Deploying Apache Airflow on Kubernetes (AKS) using Helm.
Writing DAGs in Python for ETL and data processing.
Integrating Airflow with Azure Blob Storage, Data Lake, or SQL DB.
Using KubernetesExecutor for dynamic scaling.
4. Spark with Kubernetes
Running PySpark jobs on Kubernetes clusters.
Experience with SparkSubmitOperator in Airflow for big data pipelines.
Optimizing Spark jobs for performance and cost.
Familiarity with persistent volumes and RBAC in Kubernetes for Spark workloads.
5. DevOps & Containerization
Docker — multi-stage builds for React and Python/Node apps.
Helm — templating Kubernetes manifests for multi-environment deployments.
kubectl — managing deployments, services, and pods.
CI/CD integration with Azure DevOps or GitHub Actions.
Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.