Data Engineer at NITYO INFOTECH SERVICES PTE LTD
Singapore, , Singapore -
Full Time


Start Date

Immediate

Expiry Date

30 Sep, 25

Salary

8000.0

Posted On

01 Jul, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Java, User Experience, Data Quality

Industry

Information Technology/IT

Description
  • Experience with the Systems Development Life Cycle implementation methodology (SDLC). Hands-on experience with the creation of business specification, tech specification, SIT test documentation, UAT sign off process.
  • Good knowledge of implementing ETL pipelines using Informatica BDM on data warehouses and data platforms, such as RDBMS, Snowflake .
  • Exposure and knowledge in the following technologies is advantageous:
  • SDLC Process – Confluence, JIRA, Change request, SIT/UAT
  • Big Data Platforms – Snowflake
  • OS, Programming and Scripting: Linux, Python, Shell Script
  • SQL Databases: Oracle, MS-SQL
  • Able to understand and apply the good industry practice of code versioning, testing, CICD workflow and code documentation.
  • Good communication skills required to interact with data stewards, data engineers and business users to understand the requirements.
  • Good at working with details and is meticulous for operations.

SKILLSETS REQUIRED: AWS SERVICES, JAVA

Responsibilities:

  • Understand the requirements and create the documentation for business specification, technical specifications, SIT test cases for data pipelines and internal processes following industry best practice and GIC guidelines.
  • Set up the data pipeline infrastructure strictly following technical guidelines and best practice.
  • Perform data pipeline enhancements to reduces data quality and operational issues and improve the user experience.
Responsibilities
  • Understand the requirements and create the documentation for business specification, technical specifications, SIT test cases for data pipelines and internal processes following industry best practice and GIC guidelines.
  • Set up the data pipeline infrastructure strictly following technical guidelines and best practice.
  • Perform data pipeline enhancements to reduces data quality and operational issues and improve the user experience
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