
Alan Figueroa
Azure Data Engineer
Experience of 5 years in Data Engineering, 7 years in Business Intelligence Development, 10 years in Data Analysis, 4 years in Data Science and 10 years in Financial Analysis. My main professional interest is providing data-driven solutions, analysis and skills, applied it to real world problems that generates value for the organization. High capacity of analysis oriented to achieve goals and ability to collaborate with multidisciplinary and efficient teams. In a constant search for improvement, self-learning and conscientiousness.
Careers
Senior Data Specialist
Playful Innovation Business
- Build the architecture of the Data Models to functional App, BI Reports, Machine Learning apps.
- Determine the dataflow and life cycle of data from a data model.
- Design the techincal model to the data pipeline flow inside the organization.
- Build the data model based on different databases and sources (Oracle and Azure Databases)
- Tools: SQL Server Integration Service (SSIS), Azure
Business Intelligence Specialist
MI Integration
- Data modelling & structure for Azure Data Warehouse for on premise, Oracle & SQL Databases
- Building Power BI reports and dashboards for Data Decisions of the company.
- Constant improvements of the optimization of ETL and scheduling data processes
- Manage and build new KPI for different departments: Finance, HR, Production, High Management
- Tools: Python SSIS (SQL Server Integration Services) SSAS (SQL Server Analysis Service), SIMEGO, Data
- Syncronization Studio, Azure Data Studio, Tasks Schedulers, Power BI, DAX Functions, Snowflake, SQL
- Scripts, ERP System (Oracle Database), API Service, GitHub, Python Scripts and Jupyter Notebooks.
Looker Technology Lead
Google - Infosys
- Training in the domain of ETL Process, Data Modelling with SQL, LookML and Visualizations
- with the tools of BI Looker.
- Support to clients that use the tool solving cases related to exploration, modeling and data
- extraction.
- Coordinating service request processes and tracking performance metrics.
- Tools: Look ML, SQL Codes, Connection with multiple databases (BigQuery, AWS Redshift, AWS,
- Aurora, AWS S3, Snowflake, SQL Server, PosgresSQL, etc.), Google Cloud Platform Services (GCP),
- Zendesk, Jira, Git, Snowflake, Databricks.
Education
Universidad de Sonora
Data Science
Universidad de Sonora
Finance
Universidad del Valle de México
Business Administration
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