Cloud Data Engineer

Must Have

- Industry experience in designing and implementing scalable solutions.

- Strong in object-oriented programming concepts, DSA and programming.

- Strong background in Java is a must

- Familiarity using a programming language such as Python, Go, C/C++ -> clean coding in these languages, code analysis tools.

- Strong in building CI/CD pipelines on cloud.

- Strong in RDBMS, NoSQL DB technologies like Posgresql, mongodb etc

- Experience in supporting applications post production like debugging, documentation, support.

- Building tools for automating engineering processes, data processing like SPARK.

- Taking ownership of an application as well as helping in allocating tasks to team members and unblock them from issues.

- Quick Learner and able to demonstrate POCs.

- Open to take new challenges and learn new tech-stacks and technologies.

- Hands-on experience using managed services from one or more of the major cloud vendors: AWS, GCP, Azure

- Experience with containerized platforms like docker and Kubernetes.

- Experience in designing, developing, testing, and deploying applications in the cloud.

- Experience with building orchestrations and workflow management tools such as Airflow, Prefect, Argo or Cloud native technologies like AWS Batch, Azure Data factory.

- Understanding existing code, prepare documentation and working on bug fixes and enhancements.

- Experience working with distributed processing architecture like spark etc.

- Experience in Agile and SaFe way of working.

Good to have :

- Experience in Data Engineering and Data Warehousing.

- Experience with building data pipelines on cloud.

- Experience working with Spark, Hadoop, Hive, or other Apache Foundation frameworks.

- Experience Autonomous Driving R&D applications would be added advantage.

- Experience in working on migration projects such as code migration, data migration etc.

- Experience working with spring boot framework

- Experience working on code builds such as Bazel.