Data Quality Engineer mytat.co

About Mytat.co

MYTAT is an integrated HR Solution Platform & Edtech Solution as PaaS (Platform as A Service) MYTAT enables HR Functions with Applicant Tracking System (ATS), Assessments, Lateral and Campus Hiring Solutions, and Learning Management System (LMS). Being AICTE's NEAT partner, MYTAT has reached in educational institutions across India. Powered by AI/ML technology-based engine, it has its own proprietary audio and video communication channel. Therefore, whether it is MCQ, Aptitude, Psychometric, Coding, Subjective or Psychometric assessment, MYTAT helps you with GDPR compliant standards in Managing Talent Intake and Talent Transformation. On the other hand, it provides a complete eco-system for Educational Intuitions.

Job Description

• The Informatica Data Quality Engineer (DQ Engineer) is responsible for designing, testing, deploying, and documenting the data quality procedures and their outputs.
• Throughout each project phase, the DQ Engineer provides relevant outputs and results from the data quality procedures, including any ongoing procedures that will run after project end.
• The DQ Engineer must also document at a functional level. how the procedures work within the data quality applications.
• Perform Upgrades when necessary
• Perform data load and mappings from source systems as the scope of quality information increase across the enterprise.
• Responsible for standards when creating mapplets and code migration from development through test.
• Ensure oversight and access management for the IDQ Repository.

Skills:-

• Detailed understanding of Informatica Power Center 9.5 Components and Informatica Developer Components.
• Knowledge of Informatica Data Quality standards, guidelines and best practices.
• 2+ years experience in defining and deploying data quality programs and tools on enterprise data quality projects.
• Experience in data profiling & data quality rules development using Informatica Data Quality tools.
• 2+ years of data analyst experience performing data profiling, data mapping, data validation, data manipulation, data analysis, use case, test cases, etc.