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Aleff User

@aleffuser

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Data Engineer transitioning into applied AI, building secure pipelines and RAG/LLM solutions.

Brazil

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What I'm looking for

I’m looking for an AI Data Engineering role where I can combine reliable data engineering with applied AI—RAG, agents, and LLM integration—while building automated, secure pipelines in cloud environments and collaborating with strong engineering teams.

I’m a Data Engineer focused on data pipelines, data integration, distributed processing, and cloud environments. I primarily work with Databricks and PySpark, and I’ve built reliable ingestion and transformation layers using Python and SQL.

At Capgemini, I worked with a major banking-sector client on migrating 15+ tables from Databricks (analytical layer) to Azure SQL via JDBC. I developed full and incremental pipelines orchestrated through Lakeflow Jobs, with delivery quality supported by automated CI/CD (GitHub Actions), test coverage above 90% with Pytest, and vulnerability analysis using Fortify Scan.

Previously at SONDA, I built ETL/ELT processes on Databricks using PySpark and orchestrated workflows with Apache Airflow and Azure Data Factory. I also contributed in a multi-cloud setup (AWS and Azure) and integrated SQL and NoSQL data with an emphasis on data quality, automation, consistency, and availability—while continuously strengthening my engineering best practices.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Capgemini

Jun 2025 - Present (1 year 1 month)

Worked with a major banking-sector client to migrate 15+ Databricks tables (analytical layer) to Azure SQL via JDBC. Built full and incremental data pipelines orchestrated with Lakeflow Jobs, and supported delivery quality/security using GitHub Actions CI/CD, Pytest (90%+), and Fortify Scan.

Databricks Pyspark Azure SQL JDBC Data Pipelines ETL ELT LakeFlow CI CD GitHub Actions Pytest Fortify Version Control Technical Documentation

Data Engineer

Sonda

Oct 2021 - Nov 2024 (3 years 1 month)

Built ETL/ELT processes with PySpark on Databricks and automated data workflows using Apache Airflow and Azure Data Factory. Delivered multi-cloud data integration across AWS and Azure (S3, Glue, Athena, Data Lake Storage) with a focus on data quality, consistency, and availability.