Job Description Candidate for this role is expected to provide support to the existing data management, quality and lineage solution and work closely with a dynamic team to design and implement data management & data quality-related initiatives (e.g., design/rollout of enterprise-wide data taxonomies, maintenance & implementation of solutions to facilitate data provenance & data discovery), enabling the bank to effectively leverage on data as an enterprise asset to support its strategic decision-making and actions. The function includes:
Working with relevant business units to establish additional enterprise-wide data taxonomies, to enable consistent and comprehensive data aggregation & reporting
Implementing solutions to facilitate more effective data discovery by data users
Establishing data quality (“DQ”) metrics in IBM Information Analyser (IA) tool, and applying DQ diagnostics methodology via scalable tools to assess quality of data by users as part of data discovery
Perform impact analysis based on metadata captured in the IBM Information Governance Catalogue (IGC) and assist report stakeholder to understand the data whereabouts.
Working internally with business units, data scientists and GDMO Data management and Analytics team to:
Identify opportunities for enhancements in data management capabilities, and work with relevant stakeholders to address operational or data issues in the data pipeline
Ensure data management processes comply with established framework & policies
Collaborating with IT to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation
Helping continually to improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for users.
3-5 years of related working experience, specifically in the areas of data management and quality
Prior experience IBM Information Governance Catalogue, IBM Information Analyzer, Metadex harvesting adaptors and IBM REST API module for metadata loading is a must.
Prior experience in building the taxonomies and reference data mapping is essential.
Implementation experience in data-related projects of similar scope, scale and complexity
Strong technical skills in the areas of data and database management, with experience in one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
Experience with one or more scripting language (e.g., Python, KornShell)
Experience in the reporting tools such as Qlikview or Tableau
Experience with data mining and data warehouse solutions. Knowledge in SAS and/or Teradata will be viewed favourably
Ability to deal with ambiguity and prioritise/manage multiple tasks, with good problem-solving skills
Willing to listen to multiple stakeholders and forge consensus on win-win solutions to meet sound data governance and management principles