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Open nowPosted 23 days ago

Middle Data Engineer

Sigma Software105 open roles

Where
São Paulo, SP, Brazil, Remote
Work mode
Remote
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Your applicationOpen nowMiddle Data EngineerSigma Software · São Paulo, SP, Brazil, Remote

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Sigma Software's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

13.5% of postings close within 7 days. Measured by our own scanner across the market. Sigma Software postings stay open a median of 20 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.6%3 days
  3. 13.5%7 days
  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: posted 23 days ago

Sigma Software median: 20 days open

The posting

Company Description

Do you enjoy building scalable data solutions that enable analytics, reporting, and business intelligence? We are looking for a Middle Data Engineer to join a remote team working on modern cloud-native data platforms and distributed data processing systems.

In this role, you will contribute to the development and optimization of ETL/ELT pipelines, data models, and cloud-based data architectures using technologies such as Databricks, Apache Spark, Snowflake, and AWS. This opportunity is ideal for engineers who want to deepen their expertise in modern Data Engineering practices while working on impactful business solutions.

We at Sigma Software value collaboration, continuous learning, and technical excellence. Joining our team means working in a supportive engineering environment with opportunities for professional growth, knowledge sharing, and long-term career development.

CUSTOMER

Our customer operates within a modern data-driven environment focused on analytics, reporting, and operational decision-making. The platform ecosystem combines cloud-native technologies, distributed processing frameworks, and scalable infrastructure to support reliable and high-performance data solutions.

PROJECT

The project focuses on building and maintaining scalable cloud-based data platforms that support analytics and business intelligence initiatives. The team develops ETL/ELT pipelines, optimizes data transformations, and enhances modern data architectures using distributed data processing technologies and cloud infrastructure.

Key Technologies: Python, SQL, Apache Spark, Databricks, Snowflake, AWS, ETL/ELT, CI/CD

Job Description

  • Design, develop, and maintain ETL/ELT pipelines
  • Build and optimize data transformations to support analytics and reporting needs
  • Develop and maintain data models, datasets, and integration solutions
  • Ensure data quality, consistency, and reliability through testing and monitoring
  • Troubleshoot and resolve data pipeline and performance issues
  • Collaborate with analysts, engineers, and business stakeholders to deliver data-driven solutions
  • Contribute to the development and maintenance of cloud-based data platforms
  • Participate in code reviews and technical discussions
  • Create and maintain technical documentation for implemented solutions
  • Continuously improve existing data processes and platform performance

Qualifications

  • 3+ years of experience in Data Engineering or Software Engineering
  • Upper-Intermediate English level
  • Strong SQL skills and understanding of relational and dimensional data modeling
  • Hands-on experience with Python for data processing and automation
  • Experience building and maintaining ETL/ELT pipelines
  • Hands-on experience with Databricks and Apache Spark
  • Experience working with Snowflake
  • Understanding of data warehousing and modern data platform concepts
  • Experience working with cloud environments, preferably AWS
  • Familiarity with CI/CD, Git, and software engineering best practices
  • Strong analytical, troubleshooting, and communication skills

WILL BE A PLUS

  • Experience with streaming data processing
  • Knowledge of orchestration tools such as Airflow or Dagster
  • Experience with infrastructure as code practices
  • Familiarity with data quality and observability frameworks
  • Exposure to large-scale distributed data systems
  • Experience working in Agile environments

PERSONAL PROFILE

  • Strong analytical mindset
  • Detail-oriented and quality-focused
  • Proactive and collaborative approach
  • Good communication and teamwork skills
  • Willingness to learn and grow within modern Data Engineering environments
  • Ability to work independently in remote teams
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