Timezone overlap
9h overlap with US East · Brazil
English level
Not specified
Skills & tools
Skills
Tools
About
Passionate about data and technology, always seeking new challenges for professional growth. I enjoy working on projects involving the construction and optimization of data pipelines, database modeling, and the implementation of scalable cloud solutions. I am looking for opportunities where I can contribute my data engineering experience, collaborating with dynamic teams to transform data into valuable insights. I am particularly interested in challenges related to automation, process efficiency, and data quality. Additionally, I enjoy learning new technologies and sharing knowledge with my team. For me, an ideal work environment is one where I can innovate, solve complex problems, and continue developing my skills.
Work preferences
- Job type
- Freelance / Independent, Full-time
- Company size / type
- Early-stage startup (0-20), Growth-stage startup (21-200), Large/multinational (200+), Social/Environmental Impact Company
- Culture
- Growth-stage startup (21-200)
- Industries
- E-commerce, Information Technology
- Hours
- EST business hours
- Remote experience
- I worked from Brazil for companies in the United Kingdom and the United States.
Salary context
Benchmarks for SMB non-tech role · Senior (7+ yrs).
US figures from BLS OEWS 2024 + Glassdoor; India figures from US SMB offshore vendor pricing. Adjusted for the candidate's seniority.
Work experience
- Senior Data Engineer · VerifyMyAug 2024 — Present
Designed and implemented analytics models and ETL pipelines using dbt and Airflow in Docker containers deployed on Kubernetes pods, powering dashboards in Power BI and Metabase. Led the creation of complex fact and dimension tables in dbt and…
- Senior Data Engineer · BNEXFeb 2023 — Sep 2024
Developed pipelines for the large-scale daily ingestion of Big Data, handling 30% of Brazil's food retail sales. Used SQL and PySpark within Azure Databricks notebooks to achieve a reduction in processing time by more than 30%. Leveraged Data…
- Senior Data Engineer · Farmácias APP | Delivery | By GrupoSCSep 2022 — Feb 2023
Architected a data warehouse in BigQuery with DBT and Airflow, successfully migrating and consolidating e-commerce tables, enhancing data accessibility and performance. Optimized ETL pipelines using Python, DBT, and SQL to extract data from S3…
- Data Engineer · Tok&StokAug 2021 — Sep 2022
Optimized ETL processes by consolidating data from a Snowflake Data Lake and multiple employee management platforms into a centralized Postgres data warehouse in AWS RDS, facilitating executive decision-making. Created a new People Analytics area…
- Data Analyst · Magma Engenharia do BrasilJul 2018 — Jun 2021
Led key projects across multiple industries using SQL and Python for ETL pipelines, data analysis, and reporting. Created ETL pipelines to unify diverse data sources and build analytical reports for support ticket data with Python visualization…
Education
- Bachelor of Engineering · Universidade Federal de São Carlos (UFSCar)2014—2021· Materials Science
Achievements
- Led the creation of complex fact and dimension tables in dbt and BigQuery using medallion architecture, enabling 25% faster strategic decision-making by delivering up-to-date, accessible datasets across the organization.
- Implemented Elementary observability tool for dbt models, reducing data quality issues by 60% by proactively monitoring data tests for consistency, uniqueness, anomalies, accuracy, freshness, and integrity.
- Built and maintained dashboards in Power BI and Metabase, democratizing data access and driving a 50% increase in data-driven decision-making across organizational departments.
- Collaborated closely with DevOps team to implement CI/CD best practices, streamlining deployment processes and reducing release cycles by 20% through automated testing and continuous integration.
- Identified and resolved performance issues in Airflow DAG workload distribution across Kubernetes worker pods, optimizing resource consumption and resulting in 50% cost savings and a 20% performance improvement.
- Developed pipelines for the large-scale daily ingestion of Big Data, handling 30% of Brazil's food retail sales. Used SQL and PySpark within Azure Databricks notebooks to achieve a reduction in processing time by more than 30%.
- Achieved a significant 50% reduction in storage costs by optimizing data lake structure and overutilized resources.
- Optimized ETL pipelines using Python, DBT, and SQL to extract data from S3, transform it, and load it into Amazon Redshift, achieving a 30% improvement in processing time.
- Implemented CI/CD for DBT pipelines, reducing deployment time by 60% and enhancing workflow efficiency.
- Developed automated, customized reports orchestrated with Airflow for the operations team, leading to a 40% increase in positive seller reviews and 25% higher customer retention.