About

Hello, I'm Jose Espinoza.

I’m a Data Engineer with experience in creating and maintaining data pipelines, ETL processes, API integrations, and working with cloud technologies in AWS. With hands-on experience in Python and SQL, I build scalable and efficient solutions for processing data, particularly focusing on structured and semi-structured data.

I’m skilled in working with a variety of data sources such as APIs, JSON, CSV, and relational databases. My role has involved ensuring data integration and delivering automated systems that drive business efficiency.

I’ve worked extensively in preparing datasets for Business Intelligence (BI) purposes, both for internal teams and customer-facing reports. Throughout this process, I’ve collaborated closely with stakeholders to gather requirements, understand evolving business needs, and ensure that data solutions align with their expectations. By balancing technical delivery with business priorities.

Focused On

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    Data Enginnering

    Data Storage and Modeling - ETL Processes - Data Warehousing Solutions - Big Data Technologies - Data Governance

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    Data Visualization

    Data Pipelines - Reporting - Data Insights - Dashboarding skills - Looker Studio - Power BI

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    Cloud Technologies

    Cloud Service Models - Virtualization and Containerzation - Cloud Storage and DataBases - Cloud Security and Compliance

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    Artificial Intelligence

    AI Foundations - Machine Learning Frameworks - AI Ethics - AI in Industry

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    Python

    Data Structures - Object-Oriented Programming - Python Libraries - Data Cleaning - Data Processing

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    SQL

    Database Modeling - ACID Operations - JOINS - Functions - Stored Procedures - Triggers - Query Optimization

Daniel lewis
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Resume

Education

  1. Unversidad Fidélitas

    2018 — 2023

    Bachelor's Degree in Systems Computer Enginnering/Computer Science.

    Click here to see the Degree!

  2. Coursera - IBM

    IBM Data Engineering Professional Certificate

    In Progress

Experience

  1. Data Enginner Intern at Arkose Labs

    April 2024 — Present

    - Build and maintain ETL pipelines to meet business requirements.

    - Translate business needs into technical specifications and collaborate with external technical teams to ensure smooth integrations.

    - Propose and implement data management strategies, testing architectures, and QA automation solutions.

    - Analyze raw data and experiment with new dashboarding tools to deliver automated, scalable, and high-quality data visualizations for both customer-facing and internal reports.

    - Develop and document the complete data lifecycle, including strategies for data management, pipeline workflows, and reporting automation.

    - Develop the complete data cycle in the creation of new dashboards to show value to customers. Provide fast, scalable and automated reporting.

    - Collaborate across teams, communicate technical concepts effectively, and deliver impactful data-driven insights.

    - Regularly incorporate customer feedback into data reports and dashboards to maintain relevance and accuracy in meeting their evolving business needs.

    - Proactively monitor customer data usage and satisfaction metrics to identify areas for improvement in reporting and data delivery.

My skills

  • Programming: Python, C#, .NET Core
  • Databases: SQL, PostgreSQL, SQL Server, MySQL, AWS RDS, AWS Athena, AWS Glue, Azure SQL, NoSQL Databases
  • Cloud Platforms: Azure, AWS
  • Operating Systems & Version Control: Linux, Unix, Git, GitHub
  • Data Visualization & Business Intelligence: Looker Studio, Power BI, Excel, Business Intelligence Dashboarding
  • Methodologies & Project Management Tools: Scrum, JIRA, Confluence (Documentation)
  • Data Pipeline Orchestration w/ Airflow