Java & Cloud Lead engineer- WFH

Lead Java & Cloud software engineer - WFH

This is a fully remote working opportunity.

We need some one who can join in less than 15 days .

If you are interested and fullfill the above mentioned criteria then send below information.

1. Years is relevant exp( java & cloud )

2. Notice period

3. CCTC / ECTC

4. Updated Resume with specially mentioning specified skills - GCP, Snowflake, Databricks, Azure

Must Haves : Technology Stack :

Java, SpringBoot, Cassandra, GCP, API

Your skills and experience that will help you excel

4 to 7 years of experience in Java and Cloud Software Engineering.

Proficiency in Java 17 & Spring Boot.

Experience working with distributed data-intensive platforms.

Experience working with Cloud Platforms.

Strong problem-solving and communication skills.

Experience working on Cloud platforms (GCP / Azure) and familiarity with DevOps practices.

Hands-on experience using Spark.

Familiarity with SQL Oracle / Postgres.

Experience with Spark on Databricks.

Experience with Data Lake.

Experience with automation & batch processing.

Strong hands-on experience with Java, Spring Boot, Apache Spark, and Databricks.

Proficiency in cloud environments, especially Google Cloud Platform (GCP).

Experience with distributed databases and CI / CD pipelines using Azure DevOps.

Ability to build scalable, high-performance backend systems.

Familiarity with ESG or financial data products is a plus.

Good communication and collaboration skills in agile teams.

• Must to have skillsets
• Proficiency in Java 17 & Spring Boot.
• Experience working with distributed data-intensive platforms.
• Experience working with Cloud Platforms.
• familiarity working with NoSql Database like Cassandra
• Main Tasks : Key Responsibilities
• Design and develop Java, Spring-boot microservices.
• Work proficiently with Java 17 & Spring Boot.
• Work with distributed data-intensive platforms.
• Gain experience working with Cloud Platforms.
• Solve complex problems and communicate effectively within the team.
• Work on Cloud platforms (GCP / Azure) and gain experience on DevOps practices.
• Hands-on experience using Spark is an added advantage.
• Familiarity with SQL Oracle / Postgres.
• Experience with Spark on Databricks is an added advantage.
• Experience with Data Lake.
• Experience with automation & batch processing.