Identify data gaps and enforce strong practices to promptly close any data quality issues in a timely manner; establish a single version of truth for Reference data that benefits consumers.
Proven hands-on expertise in Data Modeling, metadata management, data mapping and data lineage.
Contribute to and implement a strategy for data management in private and public cloud, leveraging cloud-native tools and techniques.
Establish and maintain Data Non-Functional Requirements (NFR) to drive completeness, accuracy, and consistency of metadata, data mappings, data lineage, and related artifacts required by Data Governance policy.
Manage data as a strategic asset and operationalize data governance, data quality, and controls across the organization.
Introduce and propagate modern Engineering practices around Data, including reusable/configurable data quality and data access control frameworks.
Drive consistency, efficiencies, and cost benefits through establishing and continuously improving Data Management practices and standards.
Qualifications:
8+ years of experience with Reference Data Management, Business Information Architecture, Analytics, Business Process re-engineering, and Product Management.
3+ years of Data Mapping and Data Lineage (create or analyze).
2+ years of technical leadership in a data and technical environment, including Data Engineering, Data Modelling, Metadata management, etc.
Strong SQL and Python Knowledge.
Ability to Ingest and use data from multiple sources.
Strong knowledge of business operational processes, data, and technology platforms.
Experience working with developers managing Sprint calls.
Ability to prioritize deliverables and manage multiple complex work streams simultaneously.
Preferences:
Database administration knowledge.
Knowledge of CB and/or CIB business functions.
Experience with JIRA, Confluence, or similar project and issue management tools.
Knowledge of AWS cloud, S3, Redshift, Spark, Iceberg, and Trino.
Education:
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics or related field.