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Data Analyst

Hello,
I'm Mia.

I transform fragmented datasets into reliable, decision-ready insights through ETL pipelines, SQL automation, and data governance.

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New York, NY

Open to work · Remote / Hybrid

Data Engineering · Analytics · ETL

B.S. Computer Science — SUNY Empire State

mianoellenavarro@gmail.com

Mia Navarro

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Mia Navarro
Data Analyst

Data Analyst specializing in data engineering, automation, and analytics. I sit at the intersection of raw data and the decisions that shape what happens next. Turning fragmented government datasets, provider records, and supply chain signals into reliable, decision-ready intelligence.

With a background spanning healthcare analytics at Elevance Health and business intelligence at Bearings Limited, I bring an end-to-end mindset.

Capabilities

Technical
Skills

Core
Data Engineering
SQL · Python · ETL Pipelines · Data Modeling · Automation · Data Quality · DuckDB · Pandas · NumPy
Visualization
BI & Reporting
Tableau · Power BI · SiSense · Chart.js · Excel · Smartsheet · MapLine · HTML Dashboards
Infrastructure
Data Systems
Microsoft SQL Server · Toad · Jupyter · Data Warehousing · Data Wrangling · SQLite · PostgreSQL · Statistical Modeling
Domain
Healthcare Systems
QNXT · Facets · LexisNexis · NPPES · CMS · HRSA · CaseTrackker · SPS · Medicaid Analytics
Work History

Professional
Experience

Elevance Health
2024 — 2026
Healthcare · Insurance
Data Analyst — Provider Data
  • Managed enterprise provider data systems across 100K+ records ensuring accuracy and compliance
  • Built SQL & Python automation for bulk updates and roster processing, reducing manual workload significantly
  • Performed compliance and data validation using LexisNexis to verify provider credentials
  • Supported acquisition transition impacting 50K+ members across provider network systems
Bearings Limited
2021 — 2022
Distribution · Supply Chain
Data Analyst — Business Intelligence
  • Built Tableau dashboards for sales, inventory, and KPI tracking across business operations
  • Developed centralized product database with 30K+ records improving data consistency
  • Automated SQL reporting pipelines reducing manual reporting workload
  • Improved data consistency and reliability across business operations
Academic

Education

Bachelor of Science
Computer Science
SUNY Empire State University
Selden, New York
Computer Science Data Analysis Statistics Algorithms Database Systems Machine Learning