Intermediate Data Engineer

Jobgether; Brasil; Presencial; BRL 120 000 - 180 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Performance bonus

Attendance bonus

Pension plan

Meal allowance

Insurance plans

Transport allowance

Childcare assistance

Days off

Medication discounts

Product discounts

WellHub partnership

Clube Ben partnership

Scholarship program

Training programs

Casual environment

Resumo da oferta

Jobgether is seeking an Intermediate Data Engineer based in Brazil to design and maintain scalable data pipelines ingesting large data volumes. You will build data transformations, APIs, and workflows across AWS/Azure/Google Cloud, improving performance and automation.

You will collaborate with stakeholders, apply best practices, and advance data platforms in a fast‑paced global setting, deepening expertise in cloud and distributed processing.

Qualificações

• Bachelor’s degree in CS or related technical discipline.
• Experience designing and implementing data pipelines and integrations.
• Strong Python, PySpark, Scala and SQL skills.
• Understanding of ETL/ELT concepts and data modeling.
• Experience with Airflow, Luigi, Mage, or Databricks Workflows.
• Experience with AWS, Azure or Google Cloud services.
• Familiarity with IaC tools like Terraform and CI/CD processes.
• Ability to build scalable, maintainable data engineering solutions.
• Strong communication and teamwork skills.
• Intermediate English proficiency.

Responsabilidades

• Implement ETL/ELT solutions across multiple systems and sources.
• Design, develop, and maintain scalable data pipelines for large data volumes.
• Apply transformations, cleaning, aggregation, and modeling techniques.
• Develop and maintain data exchange APIs between apps and data platforms.
• Build and manage pipeline workflows using Airflow, Luigi, Mage, or Databricks Workflows; use PySpark/Scala where appropriate.
• Optimize PySpark jobs and SQL queries for performance and scale.
• Follow software engineering practices: version control, testing, documentation, modular design.
• Work with AWS, Azure, Google Cloud to build cloud-based data solutions.
• Utilize Terraform, Azure DevOps, and GitHub Actions to improve pipelines.

Conhecimentos

Python

PySpark

Scala

SQL

Formação académica

Bachelor’s degree in CS/related

Ferramentas

Airflow

Luigi

Mage

Databricks Workflows

Terraform

AWS

Azure

Google Cloud

Descrição da oferta de emprego

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for anIntermediate Data Engineerbased inBrazil.

This is an opportunity to contribute to modern data engineering initiatives within a global, technology-driven environment.
You’ll build and maintain reliable data pipelines that ingest, transform, and process large volumes of information.
The role combines hands‑on engineering with opportunities to improve scalability, performance, and automation.
You’ll work across multiple data sources and cloud environments while applying strong engineering and data management practices.
Your work will help teams access trusted, well‑structured data for analysis, decision‑making, and digital transformation.
You’ll collaborate closely with technical and business stakeholders in a fast‑paced, international setting.
This role is well suited to a data engineer looking to deepen their expertise in cloud, distributed processing, and modern data platforms.

Accountabilities

• Implement ETL/ELT solutions and integrate data across multiple systems and sources, ensuring reliable and efficient data movement.
• Design, develop, and maintain scalable data pipelines for ingesting, storing, transforming, and processing large volumes of data.
• Apply data transformation, cleaning, aggregation, and modeling techniques to produce efficient and usable data structures.
• Develop and maintain data exchange APIs between applications and data platforms.
• Build and manage pipeline workflows using orchestration tools such as Apache Airflow, Luigi, Mage, or Databricks Workflows, integrating PySpark and/or Scala where appropriate.
• Optimize PySpark jobs and SQL queries by considering data volumes, query complexity, resource utilization, and overall system performance.
• Apply software engineering principles, including version control, automated testing, documentation, modular design, and maintainability.
• Work with AWS, Azure, Google Cloud, and related services to develop and operate cloud-based data solutions.
• Use automation and infrastructure tools such as Terraform, Azure DevOps, and GitHub Actions to improve development and deployment workflows.
• Collaborate with engineering and business teams to support data security, compliance, quality, and governance requirements.
• Contribute to continuous improvement initiatives that enhance the scalability, reliability, and efficiency of data processing systems.
• Communicate technical findings and solutions clearly while coordinating effectively with other teams and stakeholders.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, Systems Analysis and Development, or a related technical discipline.
• Relevant experience in data engineering, with an intermediate level of proficiency in designing and implementing data pipelines and data integration solutions.
• Strong programming skills in Python, PySpark, Scala, and SQL, with the ability to manipulate, transform, and process data effectively.
• Practical understanding of ETL/ELT concepts, data pipeline architectures, data transformation, data modeling, and distributed data processing.
• Experience with orchestration frameworks such as Apache Airflow, Luigi, Mage, or Databricks Workflows.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud and their associated data and infrastructure services.
• Familiarity with Infrastructure as Code and automation tools such as Terraform, Azure DevOps, and GitHub Actions.
• Understanding of software design principles and best practices for building maintainable and scalable data engineering solutions.
• Experience optimizing SQL queries and PySpark workloads for performance and scalability.
• Familiarity with data ingestion, transformation, analysis, and visualization tools.
• Understanding of API development and data exchange between applications.
• Strong logical reasoning, analytical thinking, and problem-solving abilities.
• Ability to work autonomously, prioritize tasks, meet deadlines, and consistently deliver high-quality work.
• Strong communication and interpersonal skills, with the ability to explain technical topics and collaborate effectively with cross-functional teams.
• Intermediate English proficiency.

Benefits

• Performance-based bonus*
• Attendance bonus*
• Private pension plan
• Meal allowance
• Health, dental, and life insurance plans
• Transportation allowance
• Childcare assistance
• Days off*
• Discounts on medications
• Discounts on company products*
• Partnership with WellHub
• Clube Ben partnership
• Scholarship program*
• School supplies support
• Language learning platforms and professional training
• Casual office environment and dress code