Rajeshwaran R

• Standardized 12 exec dashboards (Power BI) with calc groups + incremental refresh; time-to-decision cut 3 days → same-day (QBR cadence). • Implemented Power BI embedding (service principal) with Azure AD SSO + RLS for multi-tenant supplier/retailer portal (~1.2k users); zero unauthorized access incidents. • Built dbt project (68 models across stg/core/marts) on Snowflake; 120 tests (not_null, unique, relationships), daily snapshots; on-time data loads improved from 72% → 90% (8 weeks). • Partnered with CIO/data governance to certify datasets, define refresh SLAs, and reduce duplicate reports by 35%. • Automated pipeline refreshes, alerts, and stakeholder notifications using Power Automate and Snowflake tasks, reducing manual operational overhead by 40%. • Delivered a GTM analytics dashboard tracking CAC, LTV, funnel conversion, ROI, enabling budget reallocation that reduced CAC by 18%

• Built churn signals (retention model, top 10 features); retention improved 15% after targeted interventions. • Automated CSAT/NPS reporting (Python + Power BI); reporting cycle time cut 40%. • Led VOC analytics (text sentiment) → 20% drop in repeat issues; presented actions to SLT. • Owned full development lifecycle (requirements → modeling → build → QA → deployment → adoption) following enterprise guidelines and PMO change-control processes

• Consolidated payer performance/aging dashboards; reduced rework by 15%. • Built executive-ready Power BI dashboards (DAX + Power Query) that unified KPIs across 5 business units and reduced monthly reporting time by 65% • Built SQL data models + ETL; saved 5 hrs/week for finance. • Reduced data inconsistencies by implementing data contracts, lineage tracking, and certified datasets— cutting ad-hoc correction requests by 35%

• Mentored a team of analysts on data visualization best practices and advanced SQL techniques. • Collaborated with IT to optimize data warehouse performance, improving query speed. • Delivered monthly executive reports highlighting revenue cycle health, payer mix, and collection efficiency.

• Managed end-to-end revenue cycle processes • Analyzed denial trends and implemented corrective actions • Performed AR follow-up and collections

PL- 300: Microsoft Power BI Data Analyst Associate

Microsoft

Snowflake Hands-On Essentials: Data Warehousing

Snowflake

AI- 900: Azure AI Fundamentals

Microsoft