The Lead Integration Engineer will play a crucial role in modernizing the data exchange within Research and Development systems. This role focuses on integrating and building scalable, maintainable solutions to support scientific work.

Responsibilities:

Design and implement API-first architectures.
Build reusable integration capabilities.
Drive standardization of API contracts, schemas, and governance.
Lead adoption of event-based integrations using Kafka.
Implement Infrastructure as Code using Terraform.
Define CI/CD standards using GitHub Actions.
Participate in architecture and design reviews.
Mentor fellow engineers and establish best practices.

Must Haves:

10+ years of experience in software development.
Proficiency in Python and FastAPI.
Experience with Databricks and Data Lake architecture.
Understanding of REST APIs and microservices architecture.
Familiarity with event-driven architecture, particularly Kafka.
Experience with Kubernetes and Azure services.
Solid grasp of Infrastructure as Code (IaC) principles, particularly using Terraform.
Expertise in CI/CD pipelines and GitHub Actions.
Design experience in distributed systems and software development life cycle (SDLC) best practices.

Nice to Haves:

Experience in API management and Databricks Zerobus.
Knowledge of event sourcing and Apache Flink.
Familiarity with data mesh concepts.

Other Details:

Location: Warsaw (hybrid work setup).

Research Scientist, Kaggle

Research Scientist, Kaggle

Lead Integration Engineer

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