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Tier-1 brand, metro location, and mid-level data role increase applicant competition.
Strong financial services and regulatory governance focus limits cross-industry transferability.
Requires domain-specific governance, BCBS239, risk controls and advanced analytics skills, making filters stringent.
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Lead data analysis initiatives to extract actionable insights from large datasets, enabling data-driven strategic and operational decisions.
Design and implement data pipelines and automation processes for efficient data movement and processing using Python, SQL, and ETL tools.
Manage data governance and quality controls, including investigation of data issues, data lineage, and implementing improvements aligned with regulatory and risk frameworks.
Work Experience Required: Experience in Data Management, Data Governance, Data Quality Controls, preferably in financial services.
Proficiency in Python, SQL, ETL tools, and data analytics techniques including machine learning and AI.
Strong understanding of Data Governance frameworks, BCBS 239 principles, Risk and Control environments, and operational risk frameworks.
Location Requirement: Role based out of Noida, India.
Experienced in managing data quality and governance initiatives within financial services, with knowledge of financial crime or fraud data domains.
Able to collaborate effectively with cross-functional and cross-geographical stakeholders including Risk, Controls, Technology, and Data Office teams.
Demonstrates the ability to lead complex data projects and teams with a consultative, pragmatic approach focused on business value and operational risk mitigation.