Sr. Spark Software Engineer

Technology service company

Sr. Spark Software Engineer

Jobdost

Company

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Sr. Spark Software Engineer

at Technology service company

Agency job

via Jobdost

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.

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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