We are seeking a team member to lead the design and delivery of Operational Risk's data and analytics ecosystem by combining deep data engineering expertise with risk, governance, and reporting knowledge to enable data-driven risk intelligence across the organization.
In this role, you’ll make an impact in the following ways:
- Design and manage secure, scalable, and resilient data architectures that support Operational Risk reporting, analytics, governance, and regulatory requirements.
- Build and optimize end-to-end ETL/ELT pipelines using AI, Python and modern data engineering frameworks to automate ingestion and integration of data from multiple internal and external sources.
- Lead advanced data transformation and modeling using dbt and Snowflake, creating trusted, high-quality datasets that support enterprise risk reporting and analytics.
- Partner with Operational Risk, Engineering, Audit, Technology, and Business stakeholders to translate complex business requirements into scalable data and analytics solutions.
- Deliver business intelligence, reporting, dashboards,
and self-service analytics capabilities that provide actionable risk insights to management, committees, and regulatory stakeholders.
- Establish and maintain robust data governance, quality, lineage, stewardship, and control frameworks to ensure data integrity, transparency, and compliance.
- Drive Agile delivery, automation, innovation, and continuous improvement, leveraging contemporary engineering practices, AI-enabled solutions, CI/CD pipelines, and emerging technologies.
- Transform operational risk data into proactive risk intelligence that supports risk identification, trend analysis, decision-making, and broader Operational Risk Management objectives.
To be successful in this role, we’re seeking the following:
- Bachelor’s degree in computer science, Information Systems, or a related field, or an equivalent combination of education and experience.
- 6+ years of experience in Data Engineering,
📌 Vice President, Corporate Operational Risk (Pune)
🏢 BnY
📍 Pune