Java FSD + Spark

Tekskills Inc.

Dadri

Presencial

INR 3.000.000 - 5.200.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

Tekskills Inc. is seeking a senior Java FSD+Spark developer for onsite roles in Pune or Chennai. The candidate should have 6+ years of hands-on experience with Java and big data frameworks, including Spark, and be comfortable with microservices, REST APIs, and cloud environments.

You will work in a fast-paced team, contribute to scalable data processing solutions, and participate in CI/CD practices using Git. Immediate notice period is preferred.

Formación

  • Java 8/11/17 experience and strong hands-on development in full stack Java technologies.
  • Experience designing and developing scalable applications using Spark and distributed data processing.
  • Exposure to microservices, REST APIs, and cloud (AWS/Azure) environments.

Responsabilidades

  • Develop and maintain Java FSD + Spark based solutions.
  • Design scalable data processing pipelines using Spark and related big data tools.
  • Collaborate on REST APIs, microservices, and cloud deployments with CI/CD workflows.

Conocimientos

Java 8/11/17
Spring Boot
Microservices
Apache Spark
Angular
SQL
REST APIs
Kafka
Cloud
CI/CD
Git

Descripción del empleo

Job Description: Java FSD + Spark

Experience: 6+ years

Location : Pune, Chennai

Notice Period : Immediate

Mode: 5 days Onsite

Skills

Relevant Experience
Total experience

Java 8/11/17


Microservices


Apache Spark


Angular


SQL


Kafka


Java FSD + Spark requirement with 6-12 years of experience in Pune / Chennai, you can use the following screening criteria:

Mandatory Skills
  • Java 8/11/17
  • Spring Boot
  • Microservices
  • Apache Spark
  • Angular
  • SQL
  • REST APIs
  • Kafka (preferred)
  • Cloud (AWS/Azure preferred)
  • CI/CD, Git
Experience
  • Total Experience: 6 to 12 Years
  • Strong hands‑on development experience in Java Full Stack technologies
  • Experience in designing and developing scalable applications using Spark
  • Good knowledge of distributed data processing and performance tuning
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