Data Engineer (AWS+Pyspark)
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Data Engineer (AWS + pySpark)
- Having 6+ yrs 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