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Tier-1 brand, popular data lead role title, and Bangalore metro location increase candidate competition.
Role requires financial-industry data experience, platform expertise, and ontology knowledge, limiting cross-industry fit.
Explicit 10+ years data platform requirement plus domain, cloud, and leadership mandates make screening stringent.
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Lead end-to-end delivery of strategic data products and curated datasets supporting various financial crime technology programs such as AML and Investigations.
Own technical architecture and roadmap for data platforms including pipelines, semantic models, and AI-enabled automation to improve engineering productivity.
Mentor engineering teams, establish design standards, manage delivery risks, and collaborate with stakeholders to translate business requirements into scalable data solutions.
10+ years of experience in data engineering and data platform development.
At least 5 years of experience in financial industry technology and knowledge of financial services data.
3+ years of experience leading engineering teams or technical initiatives.
Expert proficiency in Python, PySpark, SQL, distributed data processing, cloud-native data architectures, and large-scale ETL frameworks.
Experienced in data modeling, dimensional modeling, and designing data products in complex financial service environments.
Familiar with knowledge graph, RDF, ontology modeling, and graph databases such as Stardog, Neo4j, or GraphDB.
Skilled in implementing data quality controls, reconciliation frameworks, and operational excellence practices in engineering teams.