Professional Journey

5+ years transforming data into business value through scalable engineering solutions

Data Engineering Excellence

Proven track record of designing and implementing enterprise-scale data solutions across diverse industries including EMS software, investment funds, banking, and aviation.

5+
Years Experience
15+
Major Projects
10+
Technologies Mastered
3
Leading Companies
DataArt Solutions, Inc. • 2022 - Present

Senior Data Engineer

Leading enterprise data engineering initiatives for Fortune 500 clients across healthcare and software industries.

📊 Enterprise Analytics & ML Data Platform

UK-based University

Implemented a scalable data platform leveraging medallion architecture to support enterprise-wide analytics and machine learning initiatives, enabling advanced data science capabilities across multiple business units.

PySpark Microsoft Fabric Azure Functions Terraform Great Expectations Analytics
  • Designed and deployed medallion architecture (Bronze, Silver, Gold layers) for structured data lake implementation
  • Developed PySpark-based data processing pipelines for large-scale analytics
  • Implemented Infrastructure as Code using Terraform for automated cloud resource provisioning and management
  • Built serverless data processing solutions with Azure Functions
  • Established comprehensive data quality framework using Great Expectations for automated testing and validation

❄️ Snowflake Data Platform Architecture

US-based EMS Software Company

Implemented a comprehensive three-layer data platform in Snowflake, serving as the backbone for external visualization tools and business intelligence.

Snowflake SQL Server Python Azure Pipelines Git
  • Designed dynamic tables across OLAP, Shared, and Reporting View layers ensuring optimal performance
  • Implemented robust debugging processes for client-reported visualization issues through comprehensive data analysis
  • Established CI/CD pipelines for seamless deployment across development and staging environments
  • Reduced data retrieval time by 40% through optimized table structures

⚡ Large-Scale XML Processing Pipeline

US-based EMS Software Company

Developed a high-performance ETL pipeline capable of processing massive volumes of nested XML files with complex transformations and dual-database loading.

Python Snowflake SQL Server Azure Functions JSON & XML Manipulation Snowpipes
  • Built Python framework applying 30+ rule-based transformations to XML data
  • Designed complete Snowflake infrastructure including tables, Snowpipes, and automated tasks
  • Created entity-relationship models spanning Stage, RAW, and OLAP layers

🔍 Investment Data Quality & Validation Framework

US-based Investment Fund

Developed a comprehensive data quality assurance system combining advanced SQL scripting with Python automation to ensure accuracy and integrity of critical investment data across multiple business systems and reporting workflows.

T-SQL Python SQL Server Data Validation & Quality ETL Scripts
  • Developed extensive suite of SQL scripts for automated data quality checks across investment portfolios and trading systems
  • Created Python automation frameworks for data manipulation, cleansing, and standardization processes
  • Implemented comprehensive data validation rules ensuring compliance with regulatory and internal standards
  • Built custom data quality monitoring dashboards using internal tools
  • Designed robust ETL scripts for seamless data integration between trading platforms and reporting systems
Unosquare • 2022

Intermediate Data Engineer

Contributed to data engineering initiatives in a dynamic startup environment.

🔄 Enterprise Event Data Integration Pipeline

US-based Fintech

Designed and implemented comprehensive SSIS-based ETL pipelines to process and integrate event data across multiple business units, providing centralized data support for enterprise-wide analytics and reporting.

SSIS T-SQL C# Data Warehousing SSRS
  • Built robust SSIS packages for automated event data extraction from multiple source systems across business units
  • Developed complex T-SQL stored procedures for data transformation and business logic implementation
  • Created standardized data models ensuring consistent event tracking across different organizational departments
  • Implemented error handling and logging mechanisms to ensure data quality and pipeline reliability
  • Established automated scheduling and monitoring for continuous data support operations
DXC Technology • 2020 - 2022

Data Engineer

Developed enterprise data solutions for banking and financial services clients, focusing on production support and scalable ETL processes.

☁️ Enterprise Cloud Migration & Lakehouse Implementation

Second Largest Airline in LATAM

Led the complete migration of critical business processes from on-premises infrastructure to Azure cloud, implementing modern lakehouse architecture with Databricks.

Azure Data Factory Databricks Blob Storage Synapse PySpark Delta Tables Power BI
  • Orchestrated end-to-end data pipeline migration using Azure Data Factory
  • Implemented lakehouse architecture on Databricks with Delta Lake optimization
  • Achieved 60% improvement in processing speed through cloud-native solutions
  • Established real-time analytics capabilities for business intelligence

✈️ Advanced Flight Rescheduling Analytics

Second Largest Airline in LATAM

Built a comprehensive analytics solution for calculating economic impact of flight rescheduling decisions, providing critical insights for operational optimization.

Python Databricks SQL Server Power BI Azure Data Factory Logic Apps
  • Designed sophisticated algorithms for flight rescheduling impact analysis
  • Created comprehensive Power BI dashboards for executive decision-making
  • Developed robust technical documentation and testing frameworks
  • Enabled data-driven decisions saving millions in operational costs

✈️ Airport Staff Planning System

Second Largest Airline in LATAM

Developed an staff planning tool that optimizes airport workforce allocation across Latin America based on real-time operational demands.

Azure Data Factory Logic Apps Databricks PySpark Spark SQL
  • Analyzed complex business requirements and translated them into functional specifications
  • Developed predictive algorithms for dynamic staff allocation across multiple airports
  • Implemented comprehensive unit testing framework ensuring reliability
  • Reduced staffing costs by 25% while improving operational efficiency
Daniel Perico