The responsibilities are detailed as below:

• Build & maintain data pipelines to support large scale data management in alignment with data strategy and data processing standards

• Experience in designing efficient and robust ETL workflows

• Experience in Database programming using multiple flavors of SQL

• Deploy scalable data pipelines for analytical needs

• Experience in Big Data ecosystem - on-prem (Hortonworks/MapR) or Cloud (Dataproc/EMR/HDInsight)

• Worked on query languages/tools such as Hadoop, Pig, SQL, Hive, Sqoop, and SparkSQL.

• Experience in any orchestration tool such as Airflow/Oozie for scheduling pipelines

• Scheduling and monitoring of Hadoop, Hive, and Spark jobs

• Basic experience in cloud environments (AWS, Azure, GCP)

• Understanding of IN memory distributed computing frameworks like Spark (and/or DataBricks) and its parameter tuning, writing optimized queries in Spark

• Experience in using Spark Streaming, Kafka and Hbase

• Experience working in an Agile/Scrum development process

PREFERRED QUALIFICATIONS

• Exposure to the latest cloud ETL tools such as Glue/ADF/Dataflow is a plus

• Expertise in data structures, distributed computing, manipulating and analyzing complex high-volume data from a variety of internal and external sources

• Experience in building structured and unstructured data pipelines

• Proficient in a programming language such as Python/Scala

• Good understanding of data analysis techniques

• Solid hands-on working knowledge of SQL and scripting

• Good understanding of relational/dimensional modeling and ETL concepts

• Understanding of any reporting tools such as Tableau, Qlikview or PowerBI

No Of Vacancy: 20
Qualification: BE/BS/MTech/MS in computer science.
Experience: 2 to 6 years of experience in building data processing applications using Hadoop, Spark and NoSQL DB and Hadoop streaming.

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