Java & Cloud Lead engineer- WFH
3 weeks ago
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.
* 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.
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