Senior Data Engineer

We are looking for a Senior Data Engineer who can design, implement, and evolve scalable data systems in AWS.

Core Responsibilities
 

• Design and implement batch and streaming data pipelines using Apache Spark.
• Build and evolve a scalable AWS-based data lake architecture.
• Develop and maintain real-time data processing systems (event-driven pipelines).
• Own performance tuning and cost optimization of Spark workloads.
• Define best practices for data modeling, partitioning, and schema evolution.
• Implement monitoring, observability, and data quality controls.
• Contribute to infrastructure automation and CI/CD for data workflows.
• Participate in architectural decisions and mentor other engineers.

RRequirements

• 5+ years of commercial experience as a Data Science / AI Engineer
• Strong Python skills and solid software engineering fundamentals
• Proven experience building high-load, production-grade systems
• 2+ years of experience working with LLM and NLP-related tasks
• Hands-on experience with RAG pipelines and vector databases
• Strong understanding of modern deep learning architectures
• Experience with at least one deep learning framework (TensorFlow or PyTorch)
• Experience with SQL and NoSQL databases
• Good knowledge of Kubernetes
• Experience working with modern AI development tools (e.g., Claude Code, Cursor)
• Upper-Intermediate or higher level of English (spoken and written)
• Familiarity with Model Context Protocol (MCP)
• Experience with production LLM frameworks (e.g., vLLM)
• Experience training or fine-tuning LLMs
• Experience with cloud platforms (AWS, Google Cloud, Azure)
• Participation in Kaggle or similar competitions