Live opening · Posted 10 hours ago

Big Data & Hadoop MapR Developer

Tata Consultancy Services (TCS) · Indore, Madhya Pradesh, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 10 hours ago
CompanyTata Consultancy Services (TCS)
LocationIndore, Madhya Pradesh, India (On-site)
Work modeNo
SkillsPython, Java
SourceLinkedin
ListedPosted 10 hours ago

About the role

Description supplied by the original job listing.

Greetings from TCS!
We’re Hiring: Big Data & Hadoop MapR Developer
Role: Developer
Primary Skill: Digital : BigData and Hadoop Ecosystem - MapR
Experience: 5–12 Years
Locations: Mumbai | Chennai | Hyderabad | Bangalore | Indore | Ahmedabad
About the Role
We are looking for experienced Big Data & Hadoop MapR Developers with strong hands-on development experience in MapR / HPE Data Fabric and Hadoop ecosystem technologies.
The role involves designing, developing, optimizing, and supporting scalable Big Data solutions and large-scale distributed data-processing applications.
Mandatory Skills
Strong hands-on development experience with MapR / HPE Data Fabric
Strong experience with Big Data and Hadoop ecosystem technologies
Hands-on experience with MapR-FS / Data Fabric File Store
Strong development experience with Apache Spark
Strong hands-on experience with Apache Hive / HiveQL
Good working knowledge of SQL
Experience with Spark SQL and DataFrames
Good understanding of HDFS APIs, YARN, and MapReduce
Strong Unix/Linux scripting experience
Experience developing large-scale distributed data-processing applications and pipelines
Strong hands-on experience in Spark and Hive debugging, troubleshooting, and performance tuning
Good understanding of SDLC and software development practices
Key Responsibilities
Design, develop, test, and maintain scalable Big Data applications in MapR / HPE Data Fabric environments.
Develop distributed data-processing solutions using MapR, Hadoop, Spark, and Hive.
Build and support reliable batch and large-scale data-processing pipelines.
Develop and optimize Spark applications, Spark SQL, Hive queries, and UDFs.
Work with high-volume structured and semi-structured datasets.
Perform debugging, troubleshooting, and performance tuning of Spark, Hive, and Big Data workloads.
Work with data ingestion, transformation, processing, storage, and workflow orchestration components.
Identify application and query performance bottlenecks and implement optimization solutions.
Participate across the SDLC, including requirements analysis, design, development, testing, deployment, and production support.
Collaborate with cross-functional teams and take ownership of assigned development deliverables.
Good-to-Have Skills
Experience with any of the following would be an added advantage:
MapR-DB / Data Fabric Database
MapR Streams / Data Fabric Event Streams
Apache Kafka
Apache HBase
Apache Sqoop
Apache Flume
Apache Oozie
Autosys or similar enterprise scheduling tools
Java and/or Python
Spark Structured Streaming
Cloud or hybrid Big Data platform exposure
Agile development methodology
Banking / BFSI domain exposure
Production support experience in Big Data environments

Work arrangement
No

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