Collibra DQ Lead

Mandatory skills: Data Quality Engineer or Data Quality Analyst, with specific expertise in Collibra Data Quality Center

Job Description:
Responsibilities:
Configure, implement, and maintain Collibra Data Quality to support data quality initiatives.
Conduct data profiling and analysis to identify data quality issues, data anomalies, and data improvement opportunities.
Collaborate with business, IT, and data governance teams to understand data quality requirements and standards.
Monitor and report on data quality trends and issues, providing actionable insights for continuous improvement.
Develop and execute data quality jobs, including regular expressions (regex) to ensure data is fit-for-purpose based on operational and business data quality requirements.
Design and implement data quality workflows, data quality scorecards, and data quality dashboards in Collibra.
Provide technical expertise and support to business users and IT teams regarding Collibra Data Quality capabilities.
Work closely with data engineers and data architects to implement data quality solutions within data pipelines and data warehouses.
Participate in data quality improvement projects, helping to identify root causes and implementing corrective actions.
Requirements:
Bachelor's degree in Computer Science, Information Systems, or a related field.
Proven experience as a Data Quality Engineer or Data Quality Analyst, with specific expertise in Collibra Data Quality Center ( Owl DQ) or other DQ tools such as Informatica, InfoAnalyzer, Ataccama.
In-depth knowledge of data quality concepts, methodologies, and best practices.
Hands-on experience in implementing and configuring Collibra Data Quality, including data quality rules, scorecards, and workflows.
Proficiency in data profiling tools and data quality assessment techniques.
Experience in configuration and connection to various data sources like Google Cloud Platform, SQL Server, SAP, etc
Familiarity with data governance principles and data stewardship processes.
Strong SQL/Spark SQL skills for data analysis and data manipulation.
Excellent problem-solving skills and attention to detail.
Self-starter with strong communication and collaboration skills to work effectively with cross-functional teams.
Ability to manage multiple priorities and meet deadlines in a fast-paced environment.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.