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Tier-1 brand, popular data role, 5+ years, metro location, and broad skills drive high competition.
Strong financial services domain knowledge and governance requirements limit cross-industry transferability.
Explicit 5+ years, domain-specific data engineering, governance and technical tool requirements make shortlisting highly strict.
Own and operate end-to-end data pipelines for operational analytics and AI-driven automation within Global Delivery simplification initiatives.
Act as data steward managing data quality, lineage, controls, and governance for core operational business services.
Collaborate with Product Owners and AI teams to enable production-grade AI workflows, ensuring data auditability, traceability, and control mechanisms before AI actions.
Minimum 5 years of hands-on data engineering experience, preferably in platform, infrastructure, or large-scale enterprise environments.
Strong proficiency in SQL and working knowledge of Python or equivalent for data processing and automation.
Experience with ETL/ELT, data warehouses/lakes, APIs, workflow orchestration, and data quality/governance in regulated domains.
Degree in Computer Science, Engineering, or equivalent practical experience in financial services domain.
Experienced in complex operational domains such as fund accounting, custody, payments, or transfer agency with cross-functional stakeholder engagement.
Capable of managing production-grade data systems integrating AI, generative AI, and agent-based workflows with strong engineering rigor.
Strategic mindset to embed data quality and governance within AI operational decisioning and business simplification contexts.