Data Engineers
Yondu, Inc.
Bonifacio Global City, Taguig City
3d ago

Job Description

  • Provides assessment and estimation of effort needed based on the provided Business request form.
  • Develops and delivers automated data pipelines (Extract, Transform, Load-ETL) jobs in the Data Lake within expected timelines.
  • Coordinates with various support groups to accomplish assigned automated data pipes for development
  • Prepare deployment package for endorsement to Release Testing Team which includes Solutions Design Document and Operations Guide.
  • Provides support during the stabilization phase of pipes endorsed to production until declared BAUeview and approves builds based on the set framework, standards, and best practices.
  • Documents source code.
  • Other job-related activities that may be assigned from time to time.
  • Job Qualifications / Requirements

  • Education At least graduate with a Bachelor’s or Master's Degree in IT, Computer Science, Engineering, or any related course.
  • Related Work Experience At least 5-8 years of Java Experience 5 years' DevOps Experience (Git, Jenkins, SonarQube, Jira) 8 years of experience in ETL development and management In-depth experience in ETL design, implementation, and support.
  • Experience with Big Data Platforms. Experience establishing and building operational data stores and analytic data stores (enterprise data warehouse)

  • Knowledge Knowledgeable in the following : In-depth knowledge on Big Data and Distributed Computing Advanced technical experience and business knowledge in various SDLC methodologies including waterfall, iterative, agile software development life cycle, or related disciplines / processes are preferred.
  • Skills : Must have strong SQL & PL / SQL skills with the ability to solve highly complex challenges Must have good communication and interpersonal skills for interacting and collaborating with developers, analysts, and business staff throughout the organization.
  • Must have the ability to communicate clearly in writing to document data requirements and translate them into technical solutions.

    Must be adept to work in a fast-paced environment with tight SLAs.

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