AWS Data Engineer

Experience - 4 to 7 yrs

Have –

·         Working on EMR, good knowledge of CDK and setting up ETL and Data pipeline

·         Coding - Python

·         AWS EMR, Athina, Supergule, Sagemaker, Sagemaker Studio

·         Data security & encryption

·         ML / AI

·  ;       Pipeline

·         Redshift

·         AWS Lambda

Expectations/Responsibility

1.      Industry experience in Data Engineering on AWS cloud with glue, redshift , Athena experience.

2.      Ability to write high quality, maintainable, and robust code, often in SQL, Scala and Python.

3.      3+ Years of Data Warehouse Experience with Oracle, Redshift, PostgreSQL, etc. Demonstrated strength in SQL, python/pyspark scripting, data modeling, ETL development, and data wareh ousing

4.      Extensive experience working with cloud services (AWS or MS Azure or GCS etc.) with a strong understanding of cloud databases (e.g. Redshift/Aurora/DynamoDB), compute engines (e.g. EMR/Glue), data streaming (e.g. Kinesis), storage (e.g. S3) etc.

5.      Experience/Exposure using big data technologies (Hadoop, Hive, Hbase, Spark, EMR, etc.)

6.      AWS engineer provides comprehensive systems administration functions on Amazon Web Services (AWS) infrastructure to include support of AWS products such as: AWS Console root user administration, Key Management, EC2 Compute, S3 Storage, Relational Database Service (RDS), AWS Networking & Content delivery (VPC, Route 53, ELB, etc.) Identity & Access Management, CloudWatch, CloudTrail, Cloud Formation, Auto Scaling, Cost and Usage Reports, and more.

Desired Skills

AWS | Big Data

Desired Candidate Profile

Qualifications

 : BACHELOR OF ENGINEERING