Mid Level Data Engineer
New
J
JobgetherSecurity & IT
BrazilFull-TimeMiddle
Salary not disclosed
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Job Details
- Languages
- Advanced English proficiency (B2+)
- Required Skills
- PythonAgileKafkaMicrosoft SQL ServerMySQLAzureDatabricksPySpark
Requirements
- Professional experience working in Data Engineering or a closely related technical field.
- Hands-on experience with Databricks and PySpark.
- Proven experience developing, maintaining, and troubleshooting data pipelines.
- Solid understanding of Data Lake concepts, data processing, and modern data engineering practices.
- Strong knowledge of Python.
- Practical experience with Microsoft Azure and cloud-based data environments.
- Familiarity with Kafka, data streaming, and data integration concepts.
- Experience working with relational or NoSQL databases such as MySQL, SQL Server, or Couchbase.
- Understanding of modern data architecture, distributed processing, and large-scale data environments.
- Experience working in Agile and international environments.
- Strong analytical and problem-solving skills.
- Ability to collaborate effectively with distributed teams and communicate technical topics clearly.
- Advanced English proficiency (B2+).
Responsibilities
- Design, develop, and maintain scalable data pipelines using Databricks and PySpark.
- Build and support data ingestion, transformation, and processing workflows within modern Data Lake environments.
- Integrate data from multiple sources, systems, and databases.
- Develop reliable, scalable, and maintainable data engineering solutions.
- Work with technologies including Python, Azure, and Kafka to support data processing and integration.
- Work with relational and NoSQL databases, including MySQL, SQL Server, and Couchbase.
- Troubleshoot data pipeline issues, identify root causes, and implement sustainable improvements.
- Contribute to the evolution of cloud-based data platforms and modern data architecture.
- Collaborate with technical teams, stakeholders, and international colleagues in an English-speaking environment.
- Participate in Agile development practices and contribute to continuous improvement across data engineering processes.
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