Sr. Data Engineer

DUTIES AND RESPONSIBILITIES:

• 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
• Prepares 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 SPECIFICATIONS:

• 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.