Establish and promote best practices for data modelling, data visualization and analytics solution design to enable consistent, high-quality outputs across the organization.
Partner with DBP to translate strategic objectives into actionable analytics use cases, ensuring clear outcomes and success metrics.
Champion the adoption of advanced analytics, AI and emerging technologies to enhance insight generation, automation and decision-making capabilities.
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Data Integration: Connect to multiple data sources (SQL Server, Oracle DB, APIs, etc.), perform complex transformations, and establish efficient data loading patterns
Change Management: Contribute to Change Request projects, supporting development, testing, and implementation activities
Minimum 3+ years of hands‑on experience in data analytics and business intelligence, ideally within banking, insurance, or financial services
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Establish data quality and service level frameworks, taking responsibility for completeness, accuracy, timeliness, consistency, and traceability; build automated reconciliation, anomaly detection, monitoring and alerting, raw data replay, backfill, and fault recovery capabilities.
Evaluate different sources (vendors, exchanges, APIs, file feeds, compliance collection) for coverage, quality, stability, revision mechanisms, and technical fit; collaborate with product, procurement, legal, and compliance teams to clarify usage, display, derivative, retention, and redistribution boundaries; drive rational primary/backup source strategies and alternatives.
Define data semantics, metric definitions, and service contracts jointly with trading product, data platform, AI engineering, and algorithm teams, ensuring consistent and reliable usage of the same stock facts across different products.
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Work with cross-functional teams to support the implementation of data governance and data management capabilities across the enterprise data platform, including data access control, data lineage, data quality, and data analytics
Coordinate with third-party vendors and internal stakeholders to support implementation and delivery activities on the data platform
Drive the implementation cloud and open-source capabilities to enable data management and data governance
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