Data Quality & Governance Consultant
Description
A Fortune 500 Company is looking for a talented Data Quality Consultant who has a
good understanding of Data Quality / Data Governance concepts, and strong
presentation skills to present and consult Senior IT/Business Leaders.
Responsibilities
- You will manage the quality of organizational data by creating, implementing, and managing data quality rules and standards.
- Analyze data in different formats, identify data quality issues, and develop methods to address these issues.
- You will be responsible for performing data cleaning, data profiling, and data analysis to ensure data consistency and accuracy.
- Take proactive approach in identifying issues related to data quality and ensure that corrective measures are implemented in a timely manner.
- You will also conduct regular data quality checks and, you will also be responsible for reviewing data accuracy, completeness, consistency, and ensuring that data is compliant with regulations.
【Company Details】
A U.S.-headquartered insurance company with offices in major cities around the world and a 40+ year history in Japan. The company focuses on creating a diverse environment, including the promotion of women, and supports their career development in Japan and abroad.
【Working Hours】
9:00 - 18:00(Mon - Fri)
*Hybrid (2 days Work from Home per week)
【Holidays】
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, and Other Special Holidays
【Services / Benefits】
Social insurance, Transportation Fee, No smoking indoors allowed (Designated smoking area), etc.
Required Skills
- A good understanding of Data Quality / Data Governance concepts.
- Experience working with various data quality tools and techniques.
- These skills include an understanding of data management and data analysis, proficiency in using data quality tools such as Ataccama, Informatica Data Quality and/or Collibra
- Strong knowledge of data modeling and database technologies like - SQL Server, Azure Synapse, Cosmos DB, Azure Data Lake, and Oracle.