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Sravya Reddy

Data Analyst • United States • s********@gmail.com • +16******054 • linkedin.com/••••• • drivetube.ai/•••••

Professional Summary

Data Analyst with 6+ years of experience designing scalable ETL pipelines, building cloud data solutions, and delivering BI for healthcare, insurance, higher education, and financial services. Skilled in SQL and Python for data engineering, with hands-on experience using Snowflake, Databricks, Azure Synapse, and IBM Db2 to integrate claims, EHR, membership, and operational datasets. Built and automated ETL with SSIS and Databricks, developed NLP text-analytics and predictive models, and produced 10+ executive Power BI dashboards to improve reporting accuracy and operational decision-making. Proven ability to implement data validation, reduce manual preparation, and convert analytic findings into operational process changes. Comfortable owning end-to-end pipelines, standardizing KPIs and governance, and partnering with QA and business stakeholders to productionize analytics at scale.

Technical Skills

Programming Language: Python,R,SQL
Databases: Snowflake,IBM Db2,Azure Synapse
Cloud Platforms: Microsoft Azure
Version Control & Development Tools: Git
Data Engineering & Processing: Azure Databricks
Data Analysis & Visualization: Pandas,NumPy,Power BI,SSRS,PL
AI/ML Frameworks & Libraries: scikit-learn
Data Integration & ETL: SQL Server Integration Services
Project Management & Collaboration: Jira
Enterprise Platforms: SharePoint
Market Research & Consumer Insights: Qualtrics

Work Experience

Blue Cross and Blue Shield of Kansas
Data Analyst Operations
February 2026 – Present
Managed healthcare operations analytics at a state Blue Cross insurer; supported membership, quality, and contact-center performance reporting and operational decision-making.
Tech Stack: SQL, Python, Power BI, IBM Db2, Snowflake, Qualtrics XM Discover
  • Analyzed large-scale operational, membership, quality, and call-center datasets using SQL and Python to produce weekly recommendations for operations leadership.
  • Designed an NLP-based text analytics framework in Python to classify member contact reasons and extract sentiment from interactions to improve routing and triage coverage.
  • Conducted correlation analysis between CSR status time, quality scores, and audit outcomes using SQL to identify drivers of service effectiveness and prioritize fixes.
  • Led development of quality-monitoring models in Qualtrics XM Discover to convert unstructured interaction data into structured quality and sentiment signals, increasing monitoring efficiency by 35%.
  • Developed interactive Power BI dashboards backed by IBM Db2 and Snowflake to track pass/fail rates, contact reasons, and performance trends and to reduce manual analysis for monthly reviews.
  • Partnered with Quality Assurance, Customer Operations, and technical teams to validate KPIs, perform root-cause analysis, and translate analytic findings into operational process changes.
Centene Corporation
Data Analyst | Business Intelligence Developer
January 2024 – February 2026
Delivered claims, pharmacy, and EHR analytics at a large managed care organization; developed ETL and BI to support clinical and operational reporting.
Tech Stack: Databricks, SSIS, Power BI, Snowflake, Azure Synapse, Python, Pandas, R
  • Developed claims and medication-adherence ETL pipelines in Databricks to integrate claims, pharmacy, and EHR sources into Snowflake for downstream reporting.
  • Created 10+ interactive Power BI dashboards with advanced DAX connected to Snowflake to improve executive visibility into claims and adherence metrics.
  • Implemented SSIS and Databricks transformations to automate ingestion into Azure Synapse and improve ETL reliability across feeds.
  • Applied Python with Pandas and NumPy for exploratory analysis to identify care-delivery trends, anomalies, and population segments for business stakeholders.
  • Connected Power BI to Azure SQL and Azure Synapse to enable automated refresh schedules and delivery consistency, improving dashboard availability and timeliness by 40%.
  • Automated R scripts to clean and preprocess large EHR and claims datasets to reduce manual preparation effort for analytics teams.
  • Coordinated enterprise data validation rules and data governance with engineering and analytics teams using SQL-based checks to increase ETL efficiency.
Pittsburg State University
Graduate Researcher
January 2023 – January 2024
Led a university research initiative to build a Student Success Analytics Platform consolidating academic and advising data for institutional planning.
Tech Stack: Python, Power BI, Pandas, scikit-learn
  • Directed development of a Student Success Analytics Platform using Python and Power BI to consolidate academic, financial, and advising data for administrators.
  • Crafted interactive Power BI dashboards to visualize retention metrics, GPA trends, and at-risk segments, increasing administrative visibility by 25%.
  • Devised predictive dropout models in Python with scikit-learn to identify at-risk students and prioritize outreach interventions.
  • Optimized preprocessing and feature-engineering workflows with Pandas to accelerate model development and reduce manual analysis time.
  • Partnered with faculty and data engineers to validate model outputs and translate analytic insights into operational advising changes.
  • Documented data lineage, feature engineering steps, and dashboard requirements to ensure reproducibility and institutional reporting standards.
Tech Mahindra
Data Analyst
January 2020 – December 2022
Supported client financial and customer analytics as part of a technology services provider; built ETL, reporting, and validation for large-scale transactional datasets.
Tech Stack: SSIS, PL, SQL, Power BI, SSRS, Git
  • Engineered 15+ ETL pipelines using SSIS and PL/SQL to consolidate financial and customer data across disparate source systems, reducing data latency for reporting.
  • Constructed interactive Power BI dashboards for loan origination, repayment, and delinquency tracking to improve stakeholder reporting efficiency.
  • Refactored complex SQL queries and stored procedures to improve query performance for high-volume reporting workloads.
  • Automated recurring financial reporting workflows with SSIS and SSRS to ensure on-time delivery for audits.
  • Implemented a data validation and monitoring framework using SQL and Excel to reduce reconciliation errors across large transaction sets.
  • Mentored junior analysts on ETL best practices, SQL performance tuning, and Git-based version control workflows to increase team productivity.

Education

Pittsburg State University
Master of Science in Information Technology • January 2023 – May 2024

Certifications

Tableau Desktop Specialist — Credly / Tableau
Foundations: Data, Data, everywhere — Coursera
SQL Beginner to Advance for Data Professionals — Code Basics
Databricks Fundamentals — Databricks

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