March 17, 2023
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Bengaluru, Karnataka, India, India
March 17, 2023
Apply NowJob description
You Will Need 4+ Years Of Experience In Developing Big Data Solutions, Including Experience With The Following
- Developing Hadoop systems.
- Loading disparate data sets and conducting pre-processing services using Hive or Pig.
- Finalizing the scope of the system and delivering Big Data solutions.
- Design, develop, document, and architect Hadoop applications
- Develop MapReduce coding that works seamlessly on Hadoop clusters
- Have working knowledge of SQL, NoSQL, data warehousing, and DBA
- Complete knowledge of the Hadoop ecosystem and Hadoop Common
- Solid Experience in ingesting the data from multiple data sources through APIs into HDFS.
- Solid Experience in creating data pipelines using NiFi
- Solid Experience dealing with different data types [structured, unstructured, semi structured] along with solid experience in dealing with different file formats [Text, Json, Avro, Parquet, ORC, etc]
- Solid experience in creating transformation using Spark, Hive on Tez and different components existing in the Hadoop eco system
- Proven Experience with Hive, Impala, NoSQL data bases querying.
- Experience on Data Modelling Star, Snowflakes. Able to apply Kimball and Inmon Methodology
- Experience with NoSQL, Hive, Impala.
- Experience in Tuning bigdata transformations using Apache Spark and Hive QL.
- Solid experience in Python, Java, Scala and SQL (including Spark SQL)
- Solid experience in creating multithreading Python, Java applications to ingest data.
- Solid experience in UNIX Bash Commands and Scripts.
- Experience with databases like Postgres, Greenplum, MYSQL, and Oracle.
- Experience in creating batch, real-time and near-real-time data pipelines.
- Experience with streaming data technologies using [ Kafka, Spark Streaming, Apache Flink, etc.]
- Align the organization?s big data solutions with their client initiatives as requested.
- Work with domain experts to put together a delivery plan with and stay on track.
- Utilize Big Data technologies to design, develop, and evolve scalable and fault-tolerant distributed components.
