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Role: Big Data & Hadoop Ecosystem Developer (MapR)
Experience: 5–12 Years
Location: Mumbai, Chennai, Hyderabad, Bangalore, Indore Ahmedabad
Job Type: Full-Time
Job Summary
Design, develop, and maintain big data solutions using the Hadoop ecosystem and MapR platform.
Build scalable ETL/ELT pipelines for structured, semi-structured, and unstructured data processing.
Develop and optimize batch and real-time data processing applications.
Implement data ingestion solutions using tools such as Kafka, Sqoop, Flume, and Nifi.
Manage and support distributed storage using MapR-FS and related technologies.
Develop Spark, Hive, and MapReduce applications for large-scale data transformation.
Monitor cluster performance and troubleshoot data processing issues.
Perform data quality validations and ensure data governance best practices.
Collaborate with data architects, analysts, and business stakeholders to understand requirements and deliver solutions.
Implement security controls, access management, and data protection mechanisms.
Support migration and modernization initiatives within the big data ecosystem.
Create technical documentation, deployment guides, and operational procedures.
Required Technical Skills
Big Data Technologies
Hadoop Ecosystem
MapR Data Platform
HDFS / MapR-FS
YARN
MapReduce
Apache Spark
Hive
HBase
Pig
Oozie
Data Ingestion & Streaming
Apache Kafka
Apache Nifi
Sqoop
Flume
Programming
Java
Scala
Python
Shell Scripting
Database Technologies
SQL
Oracle
Teradata
PostgreSQL
NoSQL Databases
Cloud & DevOps (Preferred)
AWS / Azure / GCP
Docker
Kubernetes
Jenkins
Git
Required Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
5+ years of experience in Big Data technologies.
Strong hands-on experience with MapR architecture and administration concepts.
Experience developing Spark-based data processing workflows.
Strong SQL and data modeling knowledge.
Experience working with large-scale enterprise data platforms.
Understanding of data governance, security, and compliance requirements.
Preferred Skills
Experience with cloud-based big data services.
Exposure to Databricks or modern lakehouse architectures.
Knowledge of CI/CD implementation for data engineering projects.
Experience with data migration from legacy Hadoop platforms.
Understanding of machine learning data pipelines.
Work arrangement
No
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