Sr Collibra DQ Consultant

Provide technical solutions and infrastructure to support data governance initiatives using Collibra.
Collaborate with business teams to establish data governance framework, data catalog, and lineage, and ensure compliance with privacy regulation.
Configure, implement, and maintainCollibraDGC platform to support data catalog / quality initiatives.
Conduct data profiling and data lineage / sourcing analysis to identify data quality issues, data anomalies, and data improvement opportunities.
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 requirement.
Design and implement data quality workflows, data quality scorecards, and data quality dashboards inCollibra.
Provide technical expertise and support to business users and IT teams regardingCollibraData Quality capabilities.
Work closely with data engineers and data architects to implement data quality and observability solutions within data pipelines and data warehouses.

Requirements

In-depth knowledge of data governance and quality concepts, methodologies, and best practices.
Hands-on experience in implementing and configuringCollibraData Quality, including data quality rules, scorecards, and workflows.
Exposure to data quality assessment techniques using data quality/data lineage & profiling tools as well as reliability tools like Monte Carlo, Big Eye
Experience in configuration and connection to various data sources like AWS, Oracle, DB2, etc
Familiarity with data governance and data reliability principles and data stewardship processes.
Strong SQL/Spark SQL skills for data analysis and data manipulation.
Proven experience in Collibra Data Quality Center ( Owl DQ) projects.
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.

In-depth knowledge of data governance and quality concepts, methodologies, and best practices. Hands-on experience in implementing and configuring Collibra Data Quality, including data quality rules, scorecards, and workflows. Exposure to data quality assessment techniques using data quality/data lineage & profiling tools as well as reliability tools like Monte Carlo, Big Eye Experience in configuration and connection to various data sources like AWS, Oracle, DB2, etc Familiarity with data governance and data reliability principles and data stewardship processes. Strong SQL/Spark SQL skills for data analysis and data manipulation. Proven experience in Collibra Data Quality Center ( Owl DQ) projects. 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.