Sr Spark Software Engineer

Technology service company is hiring Sr. Spark Software Engineer job (Remote only) | Cutshort

Sr. Spark Software Engineer
Technology service company
Sr. Spark Software Engineer

at Technology service company
Agency job
5
\- 10 yrs
₹10L - ₹20L / yr
Remote only
Skills
Java
J2EE
Spring Boot
Hibernate (Java)
Ansible
Git
JIRA
Apache Spark
Spark
Apache Kafka
Microservices
Kubernetes
Terraform
NOSQL Databases
API
Docker
– Bachelor’s or master’s degree in Computer Engineering, Computer Science, Computer Applications, Mathematics, Statistics, or related technical field. Relevant experience of at least 3 years in lieu of above if from a different stream of education.
– Well-versed in and 3+ hands-on demonstrable experience with: ▪ Stream & Batch Big Data Pipeline Processing using Apache Spark and/or Apache Flink.
▪ Distributed Cloud Native Computing including Server less Functions
▪ Relational, Object Store, Document, Graph, etc. Database Design & Implementation
▪ Micro services Architecture, API Modeling, Design, & Programming
– 3+ years of hands-on development experience in Apache Spark using Scala and/or Java.
– Ability to write executable code for Services using Spark RDD, Spark SQL, Structured Streaming, Spark MLLib, etc. with deep technical understanding of Spark Processing Framework.
– In-depth knowledge of standard programming languages such as Scala and/or Java.
– 3+ years of hands-on development experience in one or more libraries & frameworks such as Apache Kafka, Akka, Apache Storm, Apache Nifi, Zookeeper, Hadoop ecosystem (i.e., HDFS, YARN, MapReduce, Oozie & Hive), etc.; extra points if you can demonstrate your knowledge with working examples.
– 3+ years of hands-on development experience in one or more Relational and NoSQL datastores such as PostgreSQL, Cassandra, HBase, MongoDB, DynamoDB, Elastic Search, Neo4J, etc.
– Practical knowledge of distributed systems involving partitioning, bucketing, CAP theorem, replication, horizontal scaling, etc.
– Passion for distilling large volumes of data, analyze performance, scalability, and capacity performance issues in Big Data Platforms.
– Ability to clearly distinguish system and Spark Job performances and perform spark performance tuning and resource optimization.
– Perform benchmarking/stress tests and document the best practices for different applications.
– Proactively work with tenants on improving the overall performance and ensure the system is resilient, and scalable.
– Good understanding of Virtualization & Containerization; must demonstrate experience in technologies such as Kubernetes, Istio, Docker, OpenShift, Anthos, Oracle VirtualBox, Vagrant, etc.
– Well-versed with demonstrable working experience with API Management, API Gateway, Service Mesh, Identity & Access Management, Data Protection & Encryption.
Hands-on experience with demonstrable working experience with DevOps tools and platforms viz., Jira, GIT, Jenkins, Code Quality & Security Plugins, Maven, Artifactory, Terraform, Ansible/Chef/Puppet, Spinnaker, etc.
– Well-versed in AWS and/or Azure or and/or Google Cloud; must demonstrate experience in at least FIVE (5) services offered under AWS and/or Azure or and/or Google Cloud in any categories: Compute or Storage, Database, Networking & Content Delivery, Management & Governance, Analytics, Security, Identity, & Compliance (or) equivalent demonstrable Cloud Platform experience.
– Good understanding of Storage, Networks and Storage Networking basics which will enable you to work in a Cloud environment.
– Good understanding of Network, Data, and Application Security basics which will enable you to work in a Cloud as well as Business Applications / API services environment.
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