Senior Data Engineer

CrafTech Smart Solutions

Senior Data Engineer developing, maintaining, and optimizing data pipelines at Craf Tech. Collaborating with multidisciplinary teams and working with modern data architectures and tools.

Posted 8/1/2026full-timeSão Paulo • 🇧🇷 BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in developing and optimizing data pipelines and architectures in AWS Cloud environments, with expertise in ETL/ELT processes, data transformations using dbt, and orchestration workflows with Airflow. Strong focus on data quality, reliability, and performance in Data Lakehouse and Data Warehouse environments.

Highest-signal resume keywords

AWS Cloud ArchitecturePython DevelopmentAirflow OrchestrationDbt Data TransformationData Lakehouse Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT ProcessesData Pipeline DevelopmentData ModelingData Warehouse OptimizationApache Iceberg Knowledge

Certifications & Qualifications

Bachelor's Degree

Industry Keywords

Financial Industry Experience

Tech Stack

Tools & technologies

AirflowApacheAWSCloudETLPython

About the role

Key responsibilities & impact

Develop, maintain, and optimize data pipelines (ETL/ELT);
Design and evolve data architectures in AWS Cloud environments;
Implement and manage orchestration workflows using Airflow;
Develop data transformations and modeling using dbt;
Contribute to the design and evolution of Data Lakehouse environments;
Work with Apache Iceberg files, ensuring performance, governance, and data versioning;
Build, maintain, and optimize Data Warehouses (DW);
Ensure data quality, reliability, and performance;
Collaborate with multidisciplinary teams to gather requirements and evolve data solutions.

Requirements

What you’ll need

Bachelor's degree (completed)
Experience with Python for developing data solutions;
Knowledge of AWS (data and infrastructure services);
Experience with Airflow for pipeline orchestration;
Experience with dbt for data transformation and modeling;
Knowledge of ETL/data pipelines;
Experience with Data Lakehouse architecture;
Knowledge of Apache Iceberg;
Experience with Data Warehouse (DW) and data modeling;
Experience in the financial industry (a plus)

Benefits

Comp & perks

20 days of scheduled time off
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