Data Engineer - Scala/Spark

JD: Spark/Scala Data Engineer

Experience Range: Strictly 6-15 yrs

Required Technical Skill Set**

Hadoop, Hive, Impala, Advanced SQL, Spark, Scala, OS (Unix), CI/CD Tools (Git, Jenkins, Nexus), Agile (Jira, Confluence), Relational Databases.

Scala is Mandatory

Must-Have**

• Big Data/Hadoop Experience particularly in ingesting data and implementing Data ingestion pipelines, SQOOP, HADOOP, HDFS, HIVE, IMPALA, Java, Scala, Spark
• Scala is Mandatory
• Data Engineer with below responsibilities:
• Lead Data Engineer to build data pipelines to support implementation of data science and analytics use cases.
• Candidate needs to be able to develop code in the corresponding language (see technical skills), test it, and follow up with the implementation into Production environment.
• Candidate will also take part in the solution design phase, so experience in analysis requirements is desirable.
• Technical expert to lead a squad of engineers for a Data Product and implement data transformation projects in Hadoop.
• Candidate will lead a team of 3-5 data engineers with minimum supervision and integrate with wider IT and business project teams.

Good-to-Have

• Good exposure to Unix and HDFS commands
• Experience on Pyspark will be an added advantage
• Experience working on Data Analytics will be an added advantage
• Experience on SAS will be an added advantage

Responsibility of / Expectations from the Role

• Good work experience on Big Data Platforms like Hadoop, Spark, Scala, Hive, Impala, SQL
• Experience working on Data Engineering projects
• Good Understanding of SQL
• Good understanding of Unix and HDFS commands
• Communication
• Experience working on Data Analytics and Pyspark
• Exposure to Tableau & SAS

Regards,

Kaushik,

[phone removed].