Guillermo – Apache Airflow, Redshift, AWS

It's a DBT implementation for the recruitment automation platform.

• Integrated DBT into the existing Redshift Data Warehouse, streamlining data transformation processes and enhancing data quality;
• Translated complex transformation SQL queries into modular and maintainable DBT workflows;
• Developed comprehensive quality assurance procedures and built custom tests for DBT pipelines;
• Created documentation for DBT workflows, including data models, transformations, and scheduling, facilitating smooth onboarding and ongoing maintenance;
• Delivered a proof of concept (POC) for the first DBT model;
• Led training sessions for the team on DBT best practices.

It's a Data Warehouse implementation for the recruitment automation platform.

• Evaluated Data Warehouse technologies such as Redshift and Snowflake, including creating proof of concepts (POCs) and ultimately selecting Redshift as the preferred solution;
• Built the Data Warehouse from scratch in AWS, managing all infrastructure aspects;
• Integrated Airflow Directed Acyclic Graphs (DAGs) to work seamlessly with Redshift alongside existing systems on Postgres;
• Translated over 300 tables and transformations from Postgres to Redshift dialect;
• Conducted quality assurance for the entire migration, including custom functions;
• Monitored and troubleshoot ETL processes;
• Provided support for Metabase, creating new queries and optimizing existing ones.

The project is focused on Data Lake creation for the largest privately owned oil company in Argentina.

• Led Data Lake implementation strategy;
• Selected vendor and managed a team of 4 data scientists/engineers;
• Defined Data Model for DL (8 databases, 100's of tables);
• Built ETL model to migrate fleet data, reducing freeze time from 1 month to a few hours;
• Standardized ETL process to ingest promotion data on Dynamics Mkt;
• Supervised implementation of 2 fraud detection models.

It's a tailored Microsoft Dynamics CRM system for a major oil company's commercial sector, previously without a CRM solution.

• Managed a $4M project budget;
• Led a 30-member team, including direct reports, business reps, and vendor staff;
• Conducted a discovery phase to define the project scope;
• Handled hardware provisioning, including importing servers from another country.
• Handled business interactions with Microsoft, guaranteeing seamless cooperation;
• Recruited and managed a specialized technical team, crucial for project success.

The project is focused on a Data Warehouse establishment, which is crucial for retail operations and strategic decision-making for a major oil company.

• Set up the Data Warehouse from scratch using MS SSAS and SSIS technologies;
• Replaced the discontinued SAP data warehouse, ensuring seamless continuity of data operations;
• Established and led a BI team, fostering collaboration and expertise in data analytics and management;
• Completed the project within a tight timeframe of less than 6 months, meeting aggressive deadlines.