Big Data & Hadoop Developer

Greetings from TCS!
We’re Hiring: Big Data & Hadoop Developer
Role: Developer
Primary Skill: BigData and Hadoop Ecosystems
Experience: 5–12 Years
Locations: Mumbai | Chennai | Hyderabad | Bangalore | Indore | Ahmedabad
Job Description
We are looking for experienced Big Data & Hadoop Developers with strong hands-on expertise in designing, developing, optimizing, and supporting scalable data-processing solutions using Big Data technologies and the Hadoop ecosystem.
The ideal candidate should have strong development experience with Hadoop/HDFS, Apache Spark, Hive, SQL, Unix/Linux scripting, and large-scale distributed data-processing applications.
Must-Have Skills
Strong understanding of Big Data and distributed computing concepts
Strong hands-on experience with Hadoop and HDFS
Good understanding of YARN and MapReduce
Strong hands-on development experience with Apache Spark
Experience with Spark SQL, DataFrames, and large-scale batch processing
Strong hands-on experience with Apache Hive and HiveQL/SQL
Experience developing and optimizing Hive queries and UDFs
Strong experience with Unix/Linux scripting
Experience designing, developing, and supporting large-scale data-processing pipelines
Strong debugging, troubleshooting, and performance-tuning skills, particularly across Spark and Hive
Experience working with high-volume structured and semi-structured datasets
Good understanding of SDLC and software development practices
Big Data & Hadoop Ecosystem Skills
Experience with the following technologies will be advantageous:
Apache Sqoop for data ingestion and integration
Apache Flume for data collection and ingestion
Apache Oozie for workflow scheduling
Apache HBase for distributed NoSQL workloads
Apache Kafka for messaging and streaming use cases
Autosys or similar enterprise job-scheduling tools
Java and/or Python for Big Data application development
Key Responsibilities
Design, develop, test, and maintain scalable Big Data applications and data-processing solutions.
Develop distributed data-processing solutions using Hadoop, HDFS, Spark, and Hive.
Build and maintain reliable batch and large-scale data-processing pipelines.
Develop and optimize Spark applications, Spark SQL, Hive queries, and UDFs.
Perform debugging, troubleshooting, and performance tuning of Spark and Hive workloads.
Process and transform high-volume datasets efficiently.
Work with Hadoop ecosystem components for data ingestion, processing, and workflow orchestration.
Identify performance bottlenecks and implement appropriate optimization techniques.
Participate in requirements analysis, technical design, development, testing, deployment, and production support.
Follow established SDLC and Agile development practices.
Collaborate effectively with technical and business stakeholders.
Work independently and take ownership of assigned development deliverables.
Good-to-Have Skills
Apache Kafka and real-time/streaming data-processing concepts
Spark Structured Streaming
Apache HBase
Sqoop, Flume, and Oozie
Autosys or equivalent scheduling tools
Exposure to cloud-based Big Data environments
Banking / BFSI domain experience
Experience supporting production Big Data applications

Work arrangement
No