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Informatica Data Quality developer

Remote:

Full Remote

Contract:

Full time

Experience:

Mid-level (2-5 years)

Work from:

Brazil

Offer summary

Qualifications:

3-5 years of Informatica Data Quality experience, Experience with data profiling and validation, Knowledge of IDQ integrations and mappings, Strong analytical and problem-solving skills.

Key responsabilities:

Develop IDQ mapplets and workflows
Prepare DQ scorecards for validation

ITTConnect Startup https://ittconnect.com/

11 - 50 Employees

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Job description

This is a remote position.

ITTConnect is seeking an Informatica Data Quality Developer to work for one of our clients. This is a role with a global leader in consulting, digital transformation, technology and engineering services present in nearly 50 countries. The end client is in the food & beverage business.

Job location: Remote, work anywhere from Brazil.

This job requires excellent English, written and spoken. Please submit a resume in English and be prepared for English language interviews throughout the process.

Requirements

3-5 years, hands-on Informatica Data Quality (IDQ) development experience
Experience with DQ profiling, validation, standardization, and data cleansing with IDQ.
Experience developing DQ mapplets, workflows and roles for deploying DQ validation checks.
Knowledge and experience preparing DQ scorecards across chosen dimensions in DQ.
Experience developing source/target connection and data mapping.
Knowledge of integrations between IDQ, and Axon/EDC.
Experience developing cleanse standardization/ enrichment rules per the business.
Knowledge and experience supporting root cause for data quality errors.
Experience preparing and executing Unit Test cases.
Strong analytical and problem solving abilities.
Develop IDQ mapplets , workflows and rules for deploying data quality validation checks
Prepare DQ Scorecard for data validation across chosen dimensions of DQ
Data profiling for source data to measure as-is Data quality
Develop business validation rules to identify the exception in as-is Data sets
Develop Cleanse/Standardization/Enrichment rules as per the business recommendations
Develop source/target connection and data mapping
Prepare and Execute Unit Test cases