Job Description
The ideal candidate is a detail-oriented team player will handle all the resources and coordination from a technical standpoint. You must set and achieve objectives, ensure both top quality and control of the project, handle client and vendor interaction, and act as the subject expert.
Experience -
• Good understanding of data engineering concepts like storage, governance, cataloging, data quality, data modeling etc.
• Good understanding about various architecture patterns like data lake, data lake house, data mesh etc.
• Good understanding of Data Warehousing concepts, hands-on experience working with tools like Hive, Redshift, Snowflake, Teradata etc.
• Experience migrating or transforming legacy customer solutions to the cloud.
• Experience working with services like AWS EMR, Glue, DMS, Kinesis, RDS, Redshift, Dynamo DB, Document DB, SNS, SQS, Lambda, EKS, Data Zone etc.
• Thorough understanding of Big Data ecosystem technologies like Hadoop, PySpark, Hive, HBase etc. and other competent tools and technologies.
• Experience on Apache Airflow.
• Understanding in designing analytical solutions leveraging AWS cognitive services like Textract, Comprehend, Rekognition etc. in combination with Sagemaker is good to have.
• Experience working with modern development workflows, such as git, continuous integration/continuous deployment pipelines, static code analysis tooling, infrastructure-as-code, and more.
• Experience with a programming or scripting language – Python/Java/Scala
• AWS Professional/Specialty certification or relevant cloud expertise
• BTech degree in computer science, engineering or related field of study
Good to have:
• Experience in migrating workload from on-premise to cloud and cloud to cloud migrations
• AWS certifications
Roles & Responsibilities-
• Develop efficient ETL pipelines through spark or Glue
• Able to implement business using Python and pySpark
• Orchestrate differed Glue jobs components with Airflow along with integration with different services and tools
• Participate in code peer reviews to ensure our applications comply with best practices.
• Design highly available and scalable solution/systems dealing with considerable amount (GB/TB) of data
• Gather requirements to define AWS services and accordingly implement different security features
• Provision of different services and use those in the optimized manner with pricing understanding
• Identify and work upon incorporating Nonfunctional requirements into the solution (Performance , scalability , monitoring etc
Experience -
• Good understanding of data engineering concepts like storage, governance, cataloging, data quality, data modeling etc.
• Good understanding about various architecture patterns like data lake, data lake house, data mesh etc.
• Good understanding of Data Warehousing concepts, hands-on experience working with tools like Hive, Redshift, Snowflake, Teradata etc.
• Experience migrating or transforming legacy customer solutions to the cloud.
• Experience working with services like AWS EMR, Glue, DMS, Kinesis, RDS, Redshift, Dynamo DB, Document DB, SNS, SQS, Lambda, EKS, Data Zone etc.
• Thorough understanding of Big Data ecosystem technologies like Hadoop, PySpark, Hive, HBase etc. and other competent tools and technologies.
• Experience on Apache Airflow.
• Understanding in designing analytical solutions leveraging AWS cognitive services like Textract, Comprehend, Rekognition etc. in combination with Sagemaker is good to have.
• Experience working with modern development workflows, such as git, continuous integration/continuous deployment pipelines, static code analysis tooling, infrastructure-as-code, and more.
• Experience with a programming or scripting language – Python/Java/Scala
• AWS Professional/Specialty certification or relevant cloud expertise
• BTech degree in computer science, engineering or related field of study
Good to have:
• Experience in migrating workload from on-premise to cloud and cloud to cloud migrations
• AWS certifications
Roles & Responsibilities-
• Develop efficient ETL pipelines through spark or Glue
• Able to implement business using Python and pySpark
• Orchestrate differed Glue jobs components with Airflow along with integration with different services and tools
• Participate in code peer reviews to ensure our applications comply with best practices.
• Design highly available and scalable solution/systems dealing with considerable amount (GB/TB) of data
• Gather requirements to define AWS services and accordingly implement different security features
• Provision of different services and use those in the optimized manner with pricing understanding
• Identify and work upon incorporating Nonfunctional requirements into the solution (Performance , scalability , monitoring etc
💡 Quick Summary
Seeking a career-building opportunity? The Data Engineer position is now open for candidates interested in the Remote Jobs sector. This role in New Delhi offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Remote Jobs is a plus.
