Mid-Level Data Engineer

FCamara Consulting & Training

. Design, implement, and optimize ETL (Extract, Transform, and Load) pipelines to ensure seamless data flow between systems.

Posted 9/24/2026full-timeRemote • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing ETL pipelines, utilizing cloud services for automation, and implementing monitoring solutions to ensure data integrity and performance. Proficient in SQL and programming languages like Python or Java, with a strong understanding of cloud data architectures.

Highest-signal resume keywords

ETL Pipeline DesignApache AirflowSQL ProficiencyCloud Data ArchitectureGrafana Monitoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETLSQLPythonJavaData IntegrationCloud ServicesData ValidationWorkflow ManagementData Pipeline TestingCost Management

Tools & Technologies

Apache AirflowAWS LambdaGoogle Cloud FunctionsGrafanaS3BigQueryRedshift

Industry Keywords

Data ArchitectureData IntegrityData ProcessingCloud EnvironmentsEngineering Change Proposals

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSAzureBigQueryCloudETLGrafanaJavaPythonSQL

About the role

Key responsibilities & impact

Design, implement, and optimize ETL (Extract, Transform, and Load) pipelines to ensure seamless data flow between systems.
Use tools such as Apache Airflow to orchestrate and schedule data processing tasks.
Create and manage functions in cloud environments (e.g., AWS Lambda and Google Cloud Functions) to automate processes and handle data.
Integrate cloud data services to improve scalability and efficiency.
Configure and maintain Grafana dashboards to monitor data pipeline performance and identify potential bottlenecks.
Implement alerts and metrics to ensure data integrity and availability.
Document data processes and routines to ensure transparency and facilitate maintenance.
Participate in Engineering Change Proposals (ECPs) to propose improvements and innovations to workflows and data architecture.
Work closely with data science teams, analysts, and developers to understand requirements and ensure solutions meet business needs.
Participate in planning and review meetings to align objectives and priorities.
Implement and monitor data validation processes to ensure the quality and accuracy of information.
Conduct tests and audits of data pipelines to identify and resolve issues.

Requirements

What you’ll need

Proficiency in SQL and programming languages such as Python or Java.
Experience with ETL and data integration tools.
Strong understanding of cloud data architectures (e.g., AWS, Google Cloud, and Azure).
In-depth knowledge of Apache Airflow for workflow management.
Ability to configure and use monitoring tools such as Grafana.
Familiarity with cloud services (e.g., S3, BigQuery, and Redshift) and their best practices.
Knowledge of cost management and resource optimization in cloud environments.

Benefits

Comp & perks

This position is also open to applicants with disabilities.