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AWS Engineer

Roles & Responsibilities

  • 6-9 years of experience in data engineering
  • Experience creating and maintaining data pipeline architectures for ingestion and processing
  • Hands-on experience building ETL infrastructure using AWS data services (S3, Snowflake, Glue, Lambda) and writing complex SQL
  • Proficiency with data storage technologies (Amazon S3, SQL, NoSQL), data modeling, and PySpark; ability to optimize AWS services for cost and performance

Requirements:

  • Design, develop, and maintain scalable data pipelines using AWS Glue and PySpark
  • Create and manage ETL workflows leveraging S3, Snowflake, and other AWS data services, ensuring data quality and performance
  • Collaborate with stakeholders across multiple time zones to gather requirements and deliver data solutions
  • Monitor, optimize, and troubleshoot data pipelines and AWS resources for cost-effectiveness and reliability

Job description

Required Skills: ·
6-9 years of experience in Data Engineering ·
Creation and maintenance of optimum data pipeline architecture for ingestion, processing of data
· Creation of necessary infrastructure for ETL jobs from a wide range of data sources using, S3, Snowflake and AWS data services
· Experience in Data storage technologies like Amazon S3, SQL, NoSQL
· Hands on experience in writing complex SQL.
· Hands on experience in developing pipelines using AWS data services like Glue, Lambda · Develop, manage, and optimize data pipelines using AWS Glue and PySpark.
· Hands on experience in Optimizing AWS services for cost-effectiveness and performance.
· Data modeling technical awareness · Experience in working with stakeholders working in different time zones Good to have:
· Working knowledge on using Bigdata technologies.
· Experience in collaborating data quality and data governance team.
· Payments domain knowledge· CRM, Accounting, etc. in depth understanding
· Regulatory reporting exposure

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