Mrinal Jha

• Built and operationalized a technical-functional team of 15+ data engineers, data analysts, data visualization & functional experts across geographies with a strategic focus to create a unified & easily accessible view of enterprise data to enable data self-service and data driven decision-making for business users

• Collaborated with finance, product, sales, trading & marketing leadership across geographies to lead the design, delivery & operationalization of 50+CXO data insights views to track business performance and optimization areas

• Led the design and adoption of a centralized & integrated enterprise source of truth in the organization with 250+ monthly active users

• Designed & implemented 70+ automated data quality controls to achieve 99% data accuracy of the enterprise data

• Integrated 20+ internal & external data sources into an integrated data product to enable cross-dimensional insight generation

• Optimized the overall infrastructure cost of the underlying tech stack around AWS S3 and Databricks compute clusters with a 15% YoY cost reduction

• Formulated enterprise data strategy for leading ME bank by assessing existing data capabilities around data acquisition, data storage, data access & data consumption and designed a 3-year data roadmap for enhancing the enterprise data capabilities to align with strategic business objectives

• Championed detailed business capability assessment of 20+ capabilities across key functional & data domains such as customer experience, revenue assurance, fraud management, data & analytics for leading telecom client. Proposed future roadmap around data management & data governance domains along with adopting emerging analytics & AI solutions

• Setup Data Governance function in the client organization by defining 50+ policies & standards around data classification, data ownership, data retention, data privacy, data backup & recovery. Recommended data governance organization structure with the required roles and responsibilities. Defined data standards and best practices across the data value chain from data ingestion to data consumption for enterprise data management

• Designed the conceptual, logical and physical data model with 80+ data objects of the entire tri-party collateral management system involving Exposure, Risk, Contract Set-up, Collateral allocation & Settlement business function

• Defined Enterprise Architecture and Data Governance Framework as per TOGAF standards in all the applicable architecture domains (business, data, application & technology) for a life science research organization in Qatar

• Established Enterprise Architecture (EA) Governance practice across 3 business functions with relevant EA principles, policies, processes, checklists, and governance structure for UAE-based financial services organization

• Conceptualized and designed the Data Model (as part of Data Architecture) with 50+ data objects of the sourcing function involving suppliers, buyers and demand-supply matching for the Chinese retail company