Data Engineer
J
JobgetherSecurity & IT
Based in Brazil... allowed to work from anywhere in LATAMContractMiddle
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLAgileAzureData engineeringSparkCI/CDDatabricks
Requirements
- 5+ years of experience in data engineering or a related technical field.
- Strong hands-on experience with Microsoft Azure data services.
- Extensive experience working with Databricks and building production-grade data pipelines.
- Advanced SQL skills and proficiency in at least one programming language, preferably Python.
- Strong experience with Apache Spark and distributed data processing architectures.
- Proven ability to design, implement, and optimize scalable data workflows.
- Experience with data modeling across multiple business areas.
- Strong knowledge of version control, CI/CD pipelines, DevOps/DataOps practices, and automated testing.
- Strong analytical, debugging, and problem-solving skills.
- Ability to collaborate effectively within Agile, cross-functional engineering teams.
- Strong communication skills and ability to influence technical decisions.
Responsibilities
- Build, maintain, and optimize scalable data pipelines and workflows using modern data engineering technologies.
- Develop and manage data solutions within Databricks environments, including Delta Lake, Spark, Unity Catalog, Jobs, and Workflows.
- Design and tune distributed data processing systems to handle large-scale data workloads efficiently.
- Create and maintain complex data models across multiple business domains.
- Develop data processing solutions using SQL and programming languages, with a preference for Python expertise.
- Implement and improve CI/CD pipelines, DevOps/DataOps practices, automated testing, and engineering standards.
- Work with distributed processing technologies such as Apache Spark to support reliable data operations.
- Troubleshoot, debug, and resolve complex technical issues across multi-system environments.
- Collaborate with engineering, analytics, and business teams to deliver high-quality data solutions.
- Improve data observability, monitoring, quality processes, and platform reliability.
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