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,
8610525163.
