Data Engineer (AWS + pySpark)

Having 5+ years of relevant experience, which includes hands on experience in Big Data technologies.
Mandatory - Hands on experience in Python and PySpark.
Build pySpark applications using Spark Dataframes in Python.
Worked on optimizing spark jobs that processes huge volumes of data.
Hands on experience in version control tools like Git.
Worked on Amazon’s Analytics services like Amazon EMR, Amazon Athena, AWS Glue.
Worked on Amazon’s Compute services like Amazon Lambda, Amazon EC2 and Amazon’s Storage service like S3 and few other services like SNS.
Good to have knowledge of datawarehousing concepts – dimensions, facts, schemas- snowflake, star etc.
Have worked with columnar storage formats - Parquet etc. Well versed with compression techniques – Snappy, Gzip.
Good to have knowledge of AWS databases (atleast one) Aurora, RDS, Redshift, ElastiCache, DynamoDB.am

Data Engineer (AWS+Pyspark)

Job Description