Rupkala Patil

<p>Held programme ownership for converting multi-brand automotive data into decision systems across operations and finance.<br>
Coordinated business stakeholders, data engineering, BI, finance, and compact onsite/offshore resources to settle metric ownership, delivery priorities, and adoption needs.<br>
Positioned analytics as a control layer for fleet utilisation, profitability review, stock risk, customer lifecycle, pricing intelligence, and forecasting.<br>
Automated fleet reporting across Hertz, Moov, Thrifty, and AVR, eliminating 32+ person-hours of daily manual effort while improving visibility into fleet availability, utilisation, revenue, margin, ageing, lifecycle movement, and remarketing status.<br>
Standardised 300+ KPIs across 21+ automotive brands by aligning business definitions, calculation logic, reporting rules, and stakeholder sign-offs across New Vehicle Sales, Used Vehicle Sales, and Service Workshop operations.<br>
Built management reporting views across CRM, sales, after-sales, and finance data, enabling branch, senior management, and executive users to review pipeline, invoicing, warranty, service contract, customer, and financial performance through common KPI logic.<br>
Developed CXO-level financial reporting covering 20 KPIs across EBIT, budget, forecast, prior-year comparison, inventory value, aged stock, cash flow, and revenue leakage, supporting profitability review and corrective action planning.<br>
Created reporting-ready datasets across Databricks Silver and Gold layers, applying ingestion logic, transformation rules, refresh cycles, row-level security, KPI definitions, data dictionaries, metadata standards, and data quality controls for governed Power BI reporting.<br>
Designed a reusable finance model with 3 fact tables and 5 financial hierarchies, enabling multiple financial metrics to be produced from a common model instead of separate dashboard-specific logic.<br>
Supported BW / Tableau phase-out through impact assessment, reporting gap analysis, KPI baseline validation, and continuity planning, protecting reporting accuracy during migration to the modern analytics environment.<br>
Extended Customer 360 and Vehicle 360 into a predictive analytics pilot covering CLTV scoring, service / warranty renewal risk, Next Best Offer logic, and Power Apps-based sales enablement, with Databricks Genie configured for natural-language access to governed workspace data.<br>
Conducted Power BI training and branch-level walkthroughs, enabling business users to work with governed datasets, use interactive reporting, and reduce dependency on recurring manual reporting support.</p>

<p>Led a cross-functional team of 15+ data engineers, SAP consultants, business analysts, and QA specialists in a GCC automotive environment.<br>
Owned end-to-end technical delivery governance from backlog and sprint planning through release management and UAT, converting CDP, CRM, and integration requirements into release-ready capabilities with full traceability.<br>
Managed the roadmap and backlog for a greenfield SAP Customer Data Platform implementation, translating Customer 360, Next Best Action, Next Best Offer, customer tiering, and segmentation requirements into user stories, acceptance criteria, and release priorities.<br>
Defined 11 business-approved matching and unification rules across SAP IS-AUTO, SAP C4C CRM, and other source systems, reducing duplicate customer records and strengthening customer master-data consistency.<br>
Extended SAP CDP with a Databricks-based customer unification framework using Python and SQL, improving flexibility, transparency, and data accuracy by 18.8%.<br>
Reworked segmentation data flows using BigQuery, CDS views, and Emarsys integration to support dynamic audience creation, customer targeting, and personalised campaign execution, improving marketing effectiveness by 10.8%.<br>
Supported migration from a custom CRM application to SAP C4C by mapping lead-to-order processes, validating customer and vehicle data, and supporting integration testing across SAP C4C and SAP IS-AUTO workflows.<br>
Built analytics-ready Customer 360 and Vehicle 360 datasets by mapping VIN-level specifications, vehicle features, customer attributes, CLTV, and Next Best Offer indicators into sales and service enablement views.<br>
Designed and developed an AI-powered Lead-to-Order Copilot using Databricks, LangChain, Retrieval-Augmented Generation (RAG), Agentic AI, and SQL-based tools, enabling natural language access to enterprise data, governed AI workflows, and intelligent business decision support.</p>

<p>Managed and mentored a 10-member onsite/offshore analytics team delivering L2/L4 SAP BI/BW operations, reporting migrations, and dashboard modernisation across automotive manufacturing, healthcare, and agri-business accounts.<br>
Owned delivery governance including capacity planning, SLA adherence, incident management, and client stakeholder reporting.<br>
Established engineering standards and escalation protocols across 24/7 production environments covering BI/BW, BO, BODS, SAC, HANA, and Power BI.<br>
Managed a 10-member analyst team supporting L2/L4 BI/BW operations for Vitesco Technologies, maintaining 24/7 production coverage across process chains, scheduled jobs, reports, and business-critical analytics workflows.<br>
Optimised BI/BW process chains and solutioned a monitoring application to track production failures from a single interface, improving issue visibility during critical reporting cycles.<br>
Led BPC-to-BO reporting migration and WebI publication setup, enabling corporate reporting continuity through an integrated SAP BO environment.<br>
Migrated a 10-year-old BODS environment to the latest version for a Singapore public healthcare account, moving jobs, workflows, dataflows, databases, and documentation while supporting SAC report enhancements.<br>
Delivered Power BI dashboards for KWS Saat by preparing HANA-based datasets, creating CDS views, applying hierarchy and security logic, and securing business sign-off for extended support ownership.</p>

<p>Developed solution architecture depth across multi-client enterprise environments where legacy systems, changing business rules, and performance constraints required structured technical judgement.<br>
Built credibility in translating complex information needs into scalable delivery models across retail, telecom, financial services, and development-sector accounts.<br>
Established the architecture and implementation base later extended into SAP analytics operations, data product delivery, and KPI-led transformation roles.<br>
Delivered BusinessObjects implementation, customisation, migration, upgrade, and support projects across WebI Rich Client, IDT, CMC, RESTful Services, and BO 4.3 environments, resolving architecture and compatibility challenges.<br>
Re-engineered Java-based application logic for a flagship telecommunications client, enabling structured analysis of dealer performance, product trends, and commercial outcomes.<br>
Delivered BO / Power BI reporting for PRU CAP financial products, implementing business rules and interactive views to improve dealer-level product performance tracking.<br>
Managed John Lewis branch reporting for 3+ years, migrating 50+ reports and improving job-load performance through process-chain threading and database parallelisation.<br>
Centralised NGO / FAO programme and fundraising data through Power BI dashboards, improving targeted outcome tracking by 15% and strengthening donor, campaign, and fund-allocation visibility.</p>