Nitish Kumar Chintamaneni

About Nitish Kumar Chintamaneni

Senior Business Analyst with 9+ years of experience in delivering end-to-end BI, data analytics, and predictive solutions across healthcare, finance, insurance, and environmental domains. Specialized in Power BI, Tableau, SQL, Snowflake, ETL (SSIS, ADF, Talend), and cloud platforms (Azure, AWS, GCP).Expert in building interactive dashboards, financial analytics, healthcare claims analysis, fraud detection systems, and automated regulatory reports. Skilled in data modeling, forecasting, advanced DAX, Python integration, geospatial analysis, and real-time reporting. Proven success in•Reducing manual reporting effort by 30–50% using Power BI Service & automation•Improving investment decision-making by 20% using predictive analytics. Enhancing claims reserve accuracy by 25% via forecasting models. Implementing Row-Level Security (RLS) and ensuring HIPAA/GDPR compliance. Creating self-service reporting environments that reduced dependency on data teams by up to 40%.Strong collaboration with stakeholders, actuaries, business teams, data engineers, and clinical teams, driving data-driven decision-making and operational efficiency.

Experience

1. Senior Data Engineer

   UnitedHealth Group

   Oct 2023 — Present

   Designed and optimized high-complexity SQL transformations across Oracle, SQL Server, and Redshift to process multi-million-record healthcare datasets, ensuring high-performance execution for downstream actuarial, payment integrity, and operational analytics teams.• Engineered end-to-end Talend ETL ingestion frameworks that handle raw vendor feeds, perform cleansing, standardization, structural validation, and load curated datasets into enterprise data warehouses with strict SLA adherence.• Led data aggregation and standardization initiatives, merging claims, eligibility, and provider data across multiple source systems into unified analytical structures supporting pricing audits, reimbursement modeling, and utilization reviews.• Developed robust data quality rule engines to catch missing claim segments, invalid code sets (ICD, CPT, HCPCS), incomplete provider attributes, and inconsistent eligibility dates before they propagate into analytical data marts.• Conducted extensive data mining, anomaly detection, and root-cause investigations, tracing data issues through complex transformation chains to identify systemic mapping gaps, vendor submission issues, or ETL rule failures.• Built reliable data linking logic that reconciles 834 eligibility files with 837 claims data by validating subscriber–member relationships, coverage gaps, and policy-level dependencies to ensure accurate claim adjudication workflows.• Independently managed production pipeline deployments, monitored nightly ETL loads, and resolved critical job failures caused by schema changes, missing reference tables, or unexpected vendor file formats.• Partnered with engineering and architecture teams to debug SQL exceptions, performance bottlenecks, ETL job dependency issues, and infrastructure-level load failures, ensuring continuous availability of high-quality data pipelines.•

Education

• New England College

  Master's degree, Computer and Information Sciences and Support Services

• Andhra University College of Engineering

  Bachelor's degree, Information Technology