| 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 GCP, 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. |
