Caio M.
Data Engineer
Caio is a versatile data professional with over five years of experience spanning Software and Data Engineering, Data Science, and Analytics.
Additionally, Caio assumed a pivotal role at Nubank, where he led a team of 200 professionals, steering the Data Governance and Cost Accountability initiative. This initiative substantially enhanced the transparency of project and task-related costs, benefiting all team members involved.
During his tenure at Accenture, Caio displayed exceptional dedication as he worked diligently on implementing GCP Data solutions within clients' infrastructure. This effort profoundly impacted, significantly streamlining the data collection process from various sources and reducing the time previously spent on manual data gathering.
Main expertise
- Python 6 years
- SQL 6 years
- ETL 5 years
Other skills
- Apache Spark 4 years
- Scala 4 years
- AWS Lambda 2 years
Selected experience
Employment
Data Engineer
Nubank - 2 years 6 months
- Reformed the Social Media data collection architecture, slashing compute time and costs by over 90%.
- Spearheaded a Data Governance and Cost Accountability initiative within a 200-person team, enhancing cost visibility related to projects and tasks.
Technologies:
- Technologies:
- Python
- SQL
- ETL
- Scala
- AWS Lambda
- Data Engineering
- Bash
- Apache Airflow
- CSV
- Clojure
Data Engineer
ClearSale - 1 year 2 months
- Assisted in scaling up a new Biometry product by defining performance metrics and monitoring application behavior.
- Identified data collection gaps, enabling real-time issue awareness within the team.
- Witnessed a tenfold increase in client adoption, with monthly incoming requests surging from a few thousand to millions.
Technologies:
- Technologies:
- Python
- ETL
- Scala
- Data Engineering
- Bash
- Apache Airflow
- CSV
- Microsoft Power BI
Data Engineer
Accenture Brazil - 5 months
- Worked towards implementing GCP Data solutions on the clients' infrastructure;
- Developed a solution to gather data from 10+ data sources to create a Data Warehouse, saving time spent on manually collecting data from them;
- Helped reduce costs from third-party sources by 50% by using the raw data to develop our own Data Viz, canceling redundant Analytics contracts.
Technologies:
- Technologies:
- Python
- SQL
- ETL
- Bash
- Apache Airflow
- CSV
- Microsoft Power BI
Education
BSc.Information Systems
USP - University of São Paulo · 2017 - 2020
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