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Strong Tier-1 brand, metro location, popular mid-level data role, and broad skill requirements increase competition.
Role demands asset/wealth management domain expertise, reducing cross-industry transferability.
Mandatory 5+ years, wealth/asset management domain expertise, and specific data engineering skills create strict filters.
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Own and maintain critical data pipelines and architectures to support firm-wide business objectives within Asset and Wealth Management.
Collaborate across business, technology, and operations to provision data for AI and analytics, driving transparency, governance, and regulatory compliance.
Lead root cause analysis and remediation of data quality issues, develop proactive controls, and uplift metadata to support AI, data mesh adoption, and operational efficiency.
5+ years of applied experience with formal training or certification in software engineering.
Deep subject matter expertise in wealth and asset management data domains (customer, account, position, transaction, reference data).
Strong technical skills in data profiling, analysis, and data management with tools such as Python, R, SQL, Spark, and cloud platforms.
Experience with data lineage analysis, metadata management, data quality frameworks, and use of enterprise-authorized AI capabilities in data workflows.
Proven ability to execute in complex, matrixed environments influencing stakeholders at all levels, including executive leadership.
Experience leading strategic or transformational initiatives involving data governance, quality, or analytics transformation programs.
Skillful at integrating AI/ML technologies and agile/product management methodologies to accelerate data provisioning and governance.