Rakesh Rudraveni

About Rakesh Rudraveni

My passion lies at the intersection of data and trust. As a Data Analyst with over four years of experience in finance, healthcare, and enterprise tech, I specialize in transforming complex datasets into governed, strategic assets that drive confident decisions. I don\'t just build reports; I build the scalable, auditable data foundations that make them reliable. My approach is rooted in technical precision and business strategy. Whether enabling treasury risk analysis or HIPAA-compliant Medicaid reporting, I deliver insights that are both impactful and compliant. How I drive value:Engineered Trust & Efficiency: At BNY, I designed governed data models in Snowflake that enabled same-day delivery for 8 critical treasury reports, retiring 7 manual spreadsheets and shortening audit cycles by 5 days with Python-driven anomaly detection.Uncovered Actionable Insights: At Molina Healthcare, I built secure pipelines for 2 state Medicaid programs and analyzed 2M+ claims. The cohort trends I identified led to 4 care management updates, while automating Airflow workflows eliminated 6 manual processes.Drove Commercial Impact: At Dell Technologies, I analyzed supply chain data impacting $5-7M in hardware inventory and documented 8 recurring drivers of forecast variance that became key references for regional planning. My technical toolkit (SQL, Python, Snowflake, DBT, Airflow, Power BI/Tableau) is a means to an end: solving complex business problems. I’m a strategic partner who bridges the gap between engineering and leadership, turning data governance into a competitive advantage. I\'m eager to connect with teams who value a proactive analyst that asks the right questions and delivers answers that move the needle. Let\'s connect.Rakesh R••••••••@outlook.com+12•••75

Experience

1. Data Analyst

   BNY

   Sep 2025 — Present · US

   Designed SQL and DBT-based data models in Snowflake to support liquidity and risk reporting for treasury teams, enabling reliable access to curated datasets across 8 downstream reports within same day delivery windows. Implemented Python-driven exploratory data analysis and ML-assisted anomaly detection on financial datasets of 2M+ records, improving identification of unusual transaction patterns and shortening internal audit review cycles by 5 business days. Established governed Tableau and Power BI dashboards for stakeholders across 3 treasury functions, consolidating KPIs and retiring 7 manual spreadsheet-based reports used in recurring leadership reviews. Coordinated requirements with compliance, engineering, and risk partners through JIRA and Confluence, delivering 6 production analytics deliverables aligned with SOX controls and internal data governance standards.

Education

• Scient institute of technology

  Bachelor of Engineering - BE, Electrical and Electronics Engineering

• Eastern Illinois University

  Graduate, Computer Technology/Computer Systems Technology