Data Engineer (AWS+Pyspark)

On-siteMidData EngineerJust posted

✦Role summaryAI-generated

This role focuses on building and optimizing PySpark applications on AWS services such as EMR, Glue, and Athena, handling large-scale data pipelines. Candidates should have strong Python skills, experience with Spark DataFrames, and familiarity with AWS storage and compute services.

Skills required

Python Spark Aws emr Aws glue Aws lambda S3 Parquet Git Data warehousing AWS Snowflake Redshift

About this role

Data Engineer (AWS + pySpark)

Having 4-5 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