Java & Cloud Lead engineer- WFH

🔥 Lead Java & Cloud software engineer - WFH

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.