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Data Modeler Modeling

Location:
Salt Lake City, UT
Posted:
July 30, 2024

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Resume:

Carlos Alberto Baldemar, M.S. Mathematics

Data Architect/Engineer Incremental ETL Expert SQL Tuning Specialist http://www.linkedin.com/in/carlosbaldemar *********@*****.*** Phone 801-***-**** Orem, UT Professional Summary

Creative, intelligent, and results-oriented professional with a strong mathematical background and over 15 years of experience. Demonstrates excellent analytical and problem-solving abilities, complemented by robust business and data analysis skills. A passionate and fast learner, adept at quickly acquiring new knowledge and adapting to changing environments. Proficient in SQL performance tuning and incremental loading for ETL processes. Dedicated to producing outstanding results both independently and as part of a team. Highly skilled in customer service, fluent in both Spanish and English, and open to travel. Areas of expertise

Analysis

AWS

Azure

Business Requirements

Data Architecture

Data Bricks

Data Cleanup

Data Engineering

Data Modeling

Data Migration

Data Mining

Data Lakes

Data Lakehouse

Data Quality

Data Reconciliation

Data Science

Data Transformation

Deduplication

Dynamic SQL

ETL

Financial Analysis

General Ledger

Incremental ETL

Oracle

PL/SQL scripts

Predictive Analytics

Problem Solving

Snowflake

Solution Architecture

SQL Server

SQL Tuning

Statistical Analysis

Stored Procedures

Technical Proficiency

Unifying Data Models

Career Highlights

Rewrote the ETL Engine for HealthCatalyst and Mass General Brigham using stored procedures and Incremental Loading, achieving a 30% reduction in processing time compared to previous incremental ETL processes and more than 70% compared to full loads with some of them reaching more than 95% increase.

Developed Dynamic Visualizations in QlikView for General Ledger products at HealthCatalyst, reducing the implementation time from one month to just two days.

Became the go-to expert for SQL tuning and optimization, successfully reducing the execution time on every query requested. One example was an outlier query from over 18 hours to just 40 seconds. Job Experience

PK Title Company Location Start DTS End DTS

A Principal Data Architect Graphite Connect Thanksgiving Point, Utah Nov 2022 Jun 2024 B Data Architect Consultant HealthCatalyst South Jordan, Utah May 2014 Nov 2022 C Sr. Software Engineer/Architect RemedyInformatics Sandy, Utah Mar 2008 May 2014 FK Accomplishment

[B,C] Created a novel incremental ETL Process. By using incremental Keys, Slow Changing dimensions type 6 and Result->Data set comparisons were able to solve the issues with: Deletes, False Updates, Full loads from source. These reduced ETL run time by more than 30% on incremental loads and in full loads by more than 70% (With some up to 95% speed improvement).

[B,C] Proficiently utilized T-SQL and PL/SQL scripts generating Dynamic SQL to: Synchronize data models between more than 120 customer servers, Release data configurations between all customer servers reducing release errors from more than 20 per release to less than 1 (average).

[A] Led comprehensive data migration and transformation initiatives, ensuring seamless transition from customer data models to our proprietary internal framework. Activities included identifying and resolving duplicates and conflicts, performing data sanitization, conducting integrity validations, executing thorough data reconciliation processes alongside Data Model Migration. This improved the data onboarding process from multiple months to a few of weeks while also improving Data Sanitation and integrity.

[B] Innovated a novel approach using QlikView to enable application configuration instead of traditional customization, streamlining deployment and maintenance processes for the General Ledger and Financial Management Explorer applications. Reducing implementation times from 1 month to just 2 days.

[B] Designed and deployed a dynamic data model for Shared Cost data marts across multiple client environments, facilitating cost analysis and decision-making. Due to the nature of cost data, this dynamic data model accommodated for all different cost categories which amounted to up to 288 different combinations at the biggest customer.

[A.B,C] Trained more than 25 coworkers, minimizing onboarding time of my trainees. Education: Languages: English & Spanish

M.S. Mathematics, University of Texas at El Paso

B. S. Mathematics/minor in Chemistry (Honors – Cum Laude), University of Texas at El Paso



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