Sr. Data Engineer - AWS+Python+Pyspark Job

YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation.

At YASH, we’re a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future.

We are looking forward to hire AWS Professionals in the following areas :

AWS Data Engineer JD as below :

• Primary skillsets : AWS services including Glue, Pyspark, SQL, Databricks, Python
• Secondary skillset- Any ETL Tool, Github, DevOPs(CI-CD)
• Experience : 3-4yrs
• Degree in computer science, engineering, or similar fields
• Mandatory Skill Set : Python, PySpark , SQL, AWS with Designing , developing, testing and supporting data pipelines and applications.
• 3+ years working experience in data integration and pipeline development.
• 3+ years of Experience with AWS Cloud on data integration with a mix of Apache Spark, Glue, Kafka, Kinesis, and Lambda in S3 Redshift, RDS, MongoDB / DynamoDB ecosystems Databricks, Redshift experience is a major plus.
• 3+ years of experience using SQL in related development of data warehouse projects / applications (Oracle & amp; SQL Server)
• Strong real-life experience in python development especially in PySpark in AWS Cloud environment
• Strong SQL and NoSQL databases like MySQL, Postgres, DynamoDB, Elasticsearch
• Workflow management tools like Airflow
• AWS cloud services : RDS, AWS Lambda, AWS Glue, AWS Athena, EMR (equivalent tools in the GCP stack will also suffice)
• Good to Have : Snowflake, Palantir Foundry

At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale.

Our Hyperlearning workplace is grounded upon four principles