Engenheiro de Dados

Accountabilities:
The role is responsible for building and maintaining data engineering solutions, ensuring efficient data movement, processing, quality, and availability across the organization. Develop and maintain data ingestion pipelines, integrations, and transformation processes from multiple data sources. Build scalable data workflows using Apache Spark for both batch processing and real-time streaming scenarios. Implement and maintain event-driven data solutions using messaging and streaming technologies such as Apache Kafka and Amazon Kinesis. Extract and integrate raw data from different platforms, APIs, and databases. Design and improve transformation processes to ensure data consistency, quality, standardization, and reliability. Develop data preparation workflows, including validation, deduplication, and entity relationship management. Work with different data formats such as CSV, JSON, and TXT. Create and optimize data processes that support analytics and business consumption layers. Collaborate with technical teams to evolve data architecture and improve operational efficiency. Apply cloud-based data services and storage solutions to support scalable data environments. Requirements: The ideal candidate is a hands-on data engineer with strong experience building data pipelines, working with distributed processing technologies, and designing reliable data solutions. Professional experience in data engineering roles focused on pipeline development and data processing. Strong knowledge of Apache Spark and experience with batch and streaming data processing. Practical experience with messaging and event-driven architectures using tools such as Apache Kafka and Amazon Kinesis. Proficiency in data programming languages such as Python and/or Scala. Advanced SQL skills and experience working with complex data queries. Experience handling multiple data formats, including CSV, JSON, and TXT. Technical ability to extract and integrate data from APIs, databases, and external platforms. Experience working with data quality processes, including validation, standardization, deduplication, and entity matching. Experience with cloud data services and storage solutions, especially within AWS environments. Strong analytical thinking, problem-solving skills, and ability to collaborate with technical stakeholders. Benefits: Remote work model. Opportunity to work on modern data engineering projects involving cloud technologies and distributed systems. Hands-on experience with scalable data architectures and advanced processing frameworks. Professional growth opportunities in a technology-focused environment. Opportunity to collaborate with teams working on innovative data solutions. Exposure to industry-leading tools for data processing, streaming, and cloud infrastructure.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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