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Hadoop developer skills for your resume and career
15 hadoop developer skills for your resume and career
1. HDFS
- Developed data pipeline expending Pig and Java MapReduce to consume customer behavioral data and financial antiquities into HDFS for analysis.
- Perform transformations, clean and filter on imported data using Hive, Map Reduce, and load final data into HDFS.
2. Python
Python is a widely-known programming language. It is an object-oriented and all-purpose, coding language that can be used for software development as well as web development.
- Developed Spark application using Python on different data formats for processing and analysis.
- Developed MapReducejobs in Python for data cleaning and data processing.
3. Java
Java is a widely-known programming language that was invented in 1995 and is owned by Oracle. It is a server-side language that was created to let app developers "write once, run anywhere". It is easy and simple to learn and use and is powerful, fast, and secure. This object-oriented programming language lets the code be reused that automatically lowers the development cost. Java is specially used for android apps, web and application servers, games, database connections, etc. This programming language is closely related to C++ making it easier for the users to switch between the two.
- Developed multiple Kafka topics/queues and produced 20Million data using producer written in java.
- Designed & Implemented Java MapReduce programs to support distributed data processing.
4. HBase
- Applied Hive quires to perform analysis of vast data on HBASE using Storage Handler to meet the business requirements.
- Involved in HBASE setup and storing data into HBASE, which will be used for further analysis.
5. Sqoop
- Experienced in importing and exporting data into HDFS and assisted in exporting analyzed data to RDBMS using SQOOP.
- Perform SQOOP Incremental Import Job, Shell Script & CRONJOB for importing data into AWS S3.
6. Kafka
Kafka is a type of software that which data memory for storage, streaming, and analysis of data. This open-source software is often used to collect extensive data files for real-time data streaming to develop a new feature and create awareness of updates for new consumers or users. One of the most convenient software features is that it is reliable, fast, totally free, and designed for large networks and companies. It can run through various serves and gives them an additional storage capacity.
- Replicated data across data centers using mirror maker in Apache Kafka by doing both synchronous replication and asynchronous replication.
- Experience in maintaining and operating Kafka and monitor it consistently and effectively using cluster management tools.
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Scala is a modern programming language with multiple paradigms with which common programming models and patterns can be concisely, elegantly, and reliably expressed. Scala was created by Martin Odersky and published the first version in 2003. It combines functional and object-oriented programming in a concise high-level language. Many of Scala's design decisions are aimed at addressing criticism of Java. It interoperates seamlessly with both Java and Javascript. It is strongly seen as a static type language and does not have a primitive data concept.
- Worked on ApacheSpark along with SCALA Programming language for transferring the data in much faster and efficient way.
- Analyze data in Pig Latin, Hive and Map Reduce in Java and SCALA (SPARK).
8. Oozie
- Defined and captured metadata and rules associated with HIVE and OOZIE processes.
- Experienced in defining OOZIE job flows.
9. Cloudera
- Involved in upgrading clusters to Cloudera Distributed versions.
- Experienced with monitoring Cluster using Cloudera manager.
10. ETL
- Evaluated ETL applications to support overall performance and improvement opportunities.
- Developed ETL code using different transformations to extract, transform the data from legacy sources and load data into target system.
11. Flume
- Developed data pipeline using Flume to ingest customer behavioral data and financial histories into HDFS for analysis.
- Configured custom interceptors in Flume agents for replicating and multiplexing data into multiple sinks.
12. Hadoop Cluster
- Created and maintained Technical documentation for launching HADOOP Clusters and for executing Hive queries and PigScripts.
- Created and maintained Technical documentation for launching HADOOP Clusters and for executing Pig Scripts.
13. NoSQL
- Involved in NoSQL Cassandra database design, integration and implementation.
- Researched on Cassandra NoSQL database architecture for data read/write.
14. Hadoop Mapreduce
- Designed proof of concept on Hadoop MapReduce, Hive and Pig; demonstrated the same to the ADT team.
- Provided batch processing solution to certain unstructured and large volume of data by using Hadoop MapReduce framework.
15. Hive Queries
- Created Hive queries for performing data analysis and improving performance using tuning parameters.
- Developed Hive queries for Analysis across different multifamily application data repositories and databases.
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List of hadoop developer skills to add to your resume
The most important skills for a hadoop developer resume and required skills for a hadoop developer to have include:
- HDFS
- Python
- Java
- HBase
- Sqoop
- Kafka
- Scala
- Oozie
- Cloudera
- ETL
- Flume
- Hadoop Cluster
- NoSQL
- Hadoop Mapreduce
- Hive Queries
- Linux
- Unix
- PL/SQL
- Impala
- Hive Tables
- Visualization
- API
- Eclipse
- Data Analysis
- AWS
- BI
- Relational Databases
- JSON
- Data Lake
- Zookeeper
- Log Data
- Spark SQL
- Avro
- Data Pipeline
- Apache Spark
- XML
- Data Processing
- RDBMS
- Maven
- Continuous Integration
- POC
- Teradata
- Manage Data
- Generate Reports
- Hortonworks
- Apache Hadoop
- Data Solutions
- Jenkins
- SQL Server
- Talend
Updated January 8, 2025
