Data Engineer – Kafka

Primary Skills: Java 17+, SQL, Kafka, Spark, PostgreSQL, Oracle Exadata, Kubernetes, Airflow, Python, Data Modeling, APIs

Skill Level: Journeyman (Confirmed)

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Role Overview

Application Developer / Data Engineer responsible for designing, developing, and maintaining enterprise-grade Big Data solutions supporting customer reference and customer knowledge platforms. The role focuses on building scalable Data Products, optimizing high-volume data processing pipelines, exposing data through modern APIs and event-driven architectures, and ensuring high performance, reliability, and operational excellence in hybrid Mainframe/Cloud environments.

The ideal candidate combines strong software engineering skills with expertise in data engineering, distributed systems, and large-scale data processing.

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Key Responsibilities

• Design, develop, and maintain Big Data applications supporting enterprise customer data platforms
• Build and maintain Data Products focused on customer reference and customer knowledge domains
• Develop scalable data ingestion and processing pipelines from Mainframe to Cloud platforms
• Design and optimize complex data models for internal storage and public data exposure
• Develop and maintain REST APIs and event-driven integrations using Kafka
• Optimize SQL queries, Spark jobs, and distributed data processing performance
• Perform tuning, profiling, debugging, and root-cause analysis across distributed systems
• Participate in application modernization and continuous technology lifecycle management
• Implement automated unit, integration, and end-to-end tests
• Participate in functional validation and production deployment activities
• Perform code reviews and ensure compliance with development standards
• Estimate development effort and contribute to technical planning
• Coordinate deployments across Development, QA, and Production environments
• Produce and maintain technical documentation for production applications
• Provide technical support to architects, business analysts, and development teams
• Participate in production support and on-call activities while meeting strict SLA requirements

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Required Skills

• Strong Java development experience (Java 17 or newer)
• Strong SQL knowledge and database optimization skills
• Experience designing and maintaining Big Data platforms
• Experience working with very large datasets (hundreds of millions of records)
• Experience developing REST APIs
• Experience with Apache Kafka and event-driven architectures
• Experience with Apache Spark
• Experience with PostgreSQL and Oracle databases
• Experience with Kubernetes and Docker
• Experience with Apache Airflow
• Experience with Python for data engineering tasks
• Experience with ELK or similar monitoring platforms
• Strong tuning, profiling, and performance optimization skills
• Experience designing scalable data models
• Experience with API schema modeling (Swagger/OpenAPI)
• Knowledge of Avro schemas or similar serialization frameworks
• Experience implementing unit, integration, and end-to-end testing
• Experience performing code reviews
• Understanding of CI/CD deployment processes
• Strong analytical and troubleshooting skills

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Nice to Have

• Experience with Starburst or Trino
• Experience working in hybrid Mainframe/Cloud environments
• Experience with enterprise customer reference systems
• Knowledge of event-driven data architectures
• Experience with high-availability production environments
• Experience supporting mission-critical applications with strict SLAs
• Experience working in Agile/Scrum teams
• French language skills

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Candidate Profile

Experienced Data Engineer with strong software engineering expertise in Big Data technologies and distributed systems. Comfortable designing scalable Data Products, optimizing high-volume processing pipelines, and exposing enterprise data through APIs and event-driven platforms.

Able to work in demanding production environments, collaborate with cross-functional teams, support enterprise modernization initiatives, and deliver reliable, high-performance data solutions while maintaining excellent software quality standards.