Data Analyst Power Bi

Master of Science in Business Analytics – Northeastern University, Boston, MA, USA

Bachelor of Technology in Information Technology – VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India SATHWIK BODLA

DATA ANALYST

Ashburn, VA, USA 201-***-**** *************@*****.*** LinkedIn PROFESSIONAL SUMMARY

• Results-driven Data Analyst with proven success in extracting actionable insights from complex healthcare and financial datasets using SQL, Python, and Tableau. Skilled in data mining, data cleansing, predictive analytics, and regulatory compliance reporting.

• Expertise in designing end-to-end ETL pipelines, automating data workflows, and building interactive dashboards using Power BI, Excel, and Alteryx. Adept at KPI development, variance analysis, and forecasting to drive stakeholder decision-making and operational efficiency.

• Strong background in analyzing EMR/EHR, claims, and financial transaction data, leveraging advanced statistical models, A/B testing, and anomaly detection techniques to improve patient outcomes, fraud mitigation, and revenue cycle performance across enterprise platforms.

• Collaborated cross-functionally with data scientists, business analysts, and engineering teams in Agile environments, delivering HIPAA- compliant, scalable analytics solutions on AWS and Azure. Proficient in stakeholder communication, root cause analysis, and data storytelling. TECHNICAL SKILLS

Languages: Python, Scala, R, SQL, SAS

Packages/Libraries: NumPy, Pandas, Matplotlib, Seaborn, ggplot2, SciPy, Scikit-learn, TensorFlow Visualization Tools: Tableau, Power BI, Advanced Excel (Pivot Tables, VLOOKUP) IDEs: Visual Studio Code, PyCharm, Jupyter Notebook Database Management: MySQL, PostgreSQL, SQL, Oracle Cloud Technologies: AWS, Azure, GCP

Methodologies: SDLC, Agile, Waterfall, Predictive Modeling Version Control: Git, GitHub, Bitbucket

Data Manipulation: Data Analysis, Data Mining, Data Preprocessing, Data Mapping, Data Cleaning, Data Visualization, Data Modeling, Data Warehousing, Data Storytelling, Data Wrangling, Data Acquisition, Data Integration, Data Transformation Other Skills:

WORK EXPERIENCE

SSIS, SSRS, Machine Learning Algorithms, CI/CD, Probability Distributions, Confidence Intervals, ANOVA, Association Rules, Clustering, Advanced Analytics, ETL Processes, Informatica, Report Generation, Regression, A/B Testing, Forecasting & Modeling, Hypothesis Testing, Time Series Analysis, Root Cause Analysis Data Analyst Fidelity Investments, MA, USA Sept 2024 - Present

• Led end-to-end healthcare analytics initiatives using Power BI, BigQuery, and Python to improve payer-provider collaboration, optimize chronic care costs, and strengthen compliance across member services and regulatory reporting in a value-based care platform.

• Designed dimensional healthcare data models and optimized complex PostgreSQL queries with partitioning, window functions, and indexing to reduce claim adjudication latency and improve provider reimbursement alignment for over 15 million EDI records.

• Automated ingestion pipelines using GCP Dataflow and workflow orchestration via Cloud Composer, loading medical claims into a HIPAA- compliant BigQuery warehouse.

• Built Power BI dashboards tracking HEDIS quality metrics, wellness gaps, and plan adherence trends, empowering population health teams with interactive filters, slicers, and predictive visuals to improve program effectiveness and NCQA reporting.

• Applied SAS Macros and PROC SQL to perform healthcare cost forecasting, benchmark utilization trends, and simulate risk-adjusted capitation models, enabling finance and strategy teams to design smarter plan premiums and incentives.

• Performed feature engineering and pattern detection on multi-year claims data using Databricks and PySpark, uncovering churn indicators, chronic condition clusters, and cost anomalies to support preventive care optimization and population risk segmentation.

• Ensured HIPAA and CMS compliance using Azure Data Governance, enforcing column-level access policies, lineage tracing, and semantic data cataloging for audit readiness, risk mitigation, and enterprise-wide data stewardship alignment.

• Participated in Agile ceremonies with product owners, clinicians, and engineering teams to groom sprint backlogs, define KPIs, and deploy MVPs, aligning analytical deliverables with population health goals and compliance mandates. Data Analyst Cognizant, India Jan 2021 - Aug 2023

• Delivered financial analytics solutions by building scalable ETL pipelines using Talend, Informatica, and AWS S3/EC2, supporting high- frequency transaction ingestion, real-time fraud detection, and executive reporting for revenue assurance and financial operations.

• Modeled and orchestrated financial transformation logic using dbt, generating governed data marts for P&L reporting, liquidity risk scoring, and asset performance insights, improving data accuracy and reusability across finance and compliance teams.

• Architected interactive Tableau dashboards to visualize net margin fluctuations, segment-level profitability, and capital flow indicators, enabling finance executives to monitor fiscal KPIs and regulatory compliance performance across international business units.

• Constructed secure, CI/CD-enabled financial data pipelines using AWS CodePipeline and CloudFormation, reducing deployment time by 40% and ensuring version control for reporting assets across staging and production environments in line with SOX compliance.

• Performed exploratory data analysis and variance tracking using advanced Excel (PivotTables, conditional formatting, and data models) to identify cost anomalies and improve budget forecasting accuracy by 25%.

• Developed optimized ETL routines using SQL Server Integration Services (SSIS) and parameterized stored procedures to load and aggregate journal entries and ledger data, accelerating month-end close reporting and reducing reconciliation gaps by 30%.

• Executed real-time KPI monitoring using Amazon CloudWatch and financial alert triggers, helping finance controllers detect margin dips and transactional anomalies within seconds, minimizing operational disruptions and strengthening fiscal oversight.

• Integrated Informatica Data Quality (IDQ) to enforce schema validation, null checks, and threshold enforcement across ETL workflows, improving data reliability for automated finance dashboards and maintaining compliance with GAAP, IFRS, and internal controls. EDUCATION

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