Senior Data Engineer, Spark

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🕒 June 18

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Cadmus Soluções em TI

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1995

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

Artificial Intelligence • B2B • Enterprise

Cadmus Soluções em TI is a Brazilian IT services and solutions company that accelerates business transformation by combining human expertise and artificial intelligence. It offers Multi-AI integrations, intelligent squads (multidisciplinary teams), automation of manual processes, digital solutions including custom software development and modernization, and talent-sourcing/capacity services to staff and upskill IT teams. The company operates a Center for Artificial Intelligence and delivers tailored enterprise software, chatbots, assistants and delivery accelerators for clients across large organizations.

📋 Description

• Develop and optimize high-performance data pipelines. • Design scalable solutions for processing large volumes of data. • Contribute to the definition and evolution of the data architecture. • Implement ETL processes and integration across multiple data sources. • Work with distributed systems and event-driven architectures. • Ensure data quality, performance, and reliability. • Integrate data platforms with applications and APIs. • Participate in technical discussions and support the evolution of engineering best practices.

🎯 Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems or related fields. • Advanced English for oral and written communication. • Excellent communication and collaboration skills across technical and business teams. • Minimum of 7 years of professional experience in Technology. • At least 5 years of hands-on experience as a Data Engineer using Apache Spark. • Mandatory Technical Knowledge • Data Engineering • ETL/ELT • Apache Spark • PySpark • Distributed data processing • Data modeling and integration • Messaging and Streaming • Apache Kafka • Real-time event processing • Databases • Relational databases (SQL) • NoSQL databases • Architecture and Platform • System Architecture • Distributed Systems • REST APIs • Cloud Computing • Application integration