Remote Data Engineer

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TWO95 International

๐Ÿ“Remote - India

Job highlights

Summary

Join our team as a Data Engineer and work on designing and implementing core data analytic platform components, maintaining and designing common data flow pipelines, and supporting and troubleshooting data flow activities on cloud data warehouse environments.

Requirements

  • Bachelorโ€™s degree in computer Science or related field
  • 5-7 yearsโ€™ experience in the following: Snowflake, Databricks management
  • Python and AWS Lambda
  • Scala and/or Java
  • Data integration service, SQL and Extract Transform Load (ELT)
  • Azure or AWS for development and deployment
  • Jira or similar tool during SDLC
  • Experience managing codebase using Code repository in Git/GitHub or Bitbucket
  • Experience working with a data warehouse
  • Familiarity with structured and semi-structured data formats including JSON, Avro, ORC, Parquet, or XML
  • Exposure to working in an agile work environment

Responsibilities

  • Design and implement core data analytic platform components that would be shared extended to different analytics group
  • Review approaches and completed data pipelines against platform best practices and patterns
  • Maintain and design a common data flow pipeline data transformation activities such as Extract Transform Load (ETL)
  • Support and troubleshoot the data flow activities on cloud data warehouse environments
  • Develop data pipeline code using Python, Java, AWS Lambda and/or Azure Data Factory
  • Perform requirements planning, monitoring, and end-to-end requirements management throughout the data asset development life-cycle
  • Direct and help other developers and analyst to ensure data platform patterns are adhered. Designing, building, and documenting RESTful API using OpenAPI specification tools such as Swagger

Job description

Title: Data Engineer

Job Type: Contract

Location: 100% Remote work (India)

Salary: (INR)Open/Market

Responsibilities :

  • Design and implement core data analytic platform components that would be shared extended to different analytics group.
  • Review approaches and completed data pipelines against platform best practices and patterns.
  • Maintain and design a common data flow pipeline data transformation activities such as Extract Transform Load (ETL).
  • Support and troubleshoot the data flow activities on cloud data warehouse environments.
  • Develop data pipeline code using Python, Java, AWS Lambda and/or Azure Data Factory
  • Perform requirements planning, monitoring, and end-to-end requirements management throughout the data asset development life-cycle.
  • Direct and help other developers and analyst to ensure data platform patterns are adhered.
    • Designing, building, and documenting RESTful API using OpenAPI specification tools such as Swagger
    • Microsoft PowerBI
    • Snowflake Data warehouse, MS SQL Data warehouse
    • Apache Spark or Hadoop
    • SparkR
    • Linux/PowerShell scripting
    • AWS Lambda or Azure function

Desired Skills :

Required Experience :

  • Bachelorโ€™s degree in computer Science or related field
  • 5-7 yearsโ€™ experience in the following:
    • Snowflake, Databricks management,
    • Python and AWS Lambda
    • Scala and/or Java
    • Data integration service, SQL and Extract Transform Load (ELT)
    • Azure or AWS for development and deployment
    • Jira or similar tool during SDLC
    • Experience managing codebase using Code repository in Git/GitHub or Bitbucket
  • Experience working with a data warehouse.
  • Familiarity with structured and semi-structured data formats including JSON, Avro, ORC, Parquet, or XML
  • Exposure to working in an agile work environment.

If interested please send your updated resume to : [email protected] and include your rate/Salary requirement along with your contact details with a suitable time when we can reach you. If you know of anyone in your sphere of contacts, who would be a perfect match for this job then, we would appreciate if you can forward this posting to them with a copy to us.

We look forward to hearing from you at the earliest.

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