Job VC
Senior Data Engineer
Technologies
Description
We are looking for a Senior Data Engineer.
This is not a standard ETL role. You will work on a high-load system processing 10,000+ executions per minute, building scalable pipelines where AI and LLM logic are embedded directly into production data flows.
The role combines data engineering, backend thinking, infrastructure ownership, and real production AI integration.
What you will do:
Design and maintain scalable data pipelines in Python on Google Cloud Platform
Build and optimize AI-driven scoring flows using LLMs for real-time identity enrichment
Work with BigQuery, Apache Spark, and Apache Iceberg for heavy data processing
Maintain high-load orchestration with custom Python nodes and complex workflows
Own deployment and release processes (CI/CD)
Optimize PostgreSQL performance under heavy load
Investigate incidents and resolve root causes permanently
Use AI engineering tools such as Claude in daily development
Requirements:
4+ years of experience in Data Engineering / Backend Engineering
Strong Python skills
Commercial experience with production LLM integration (OpenAI / Anthropic / Gemini)
Strong knowledge of GCP (Cloud Functions, IAM, Networking)
Experience with BigQuery, Spark, Iceberg
Good understanding of Kubernetes
Experience with workflow orchestration tools (n8n is a strong plus)
Strong practical knowledge of PostgreSQL
English level B2+
What is important for us:
Ownership mindset
Fast learning ability
Strong problem-solving approach
Active AI usage in engineering work
Focus on practical results over unnecessary complexity
This is not a standard ETL role. You will work on a high-load system processing 10,000+ executions per minute, building scalable pipelines where AI and LLM logic are embedded directly into production data flows.
The role combines data engineering, backend thinking, infrastructure ownership, and real production AI integration.
What you will do:
Design and maintain scalable data pipelines in Python on Google Cloud Platform
Build and optimize AI-driven scoring flows using LLMs for real-time identity enrichment
Work with BigQuery, Apache Spark, and Apache Iceberg for heavy data processing
Maintain high-load orchestration with custom Python nodes and complex workflows
Own deployment and release processes (CI/CD)
Optimize PostgreSQL performance under heavy load
Investigate incidents and resolve root causes permanently
Use AI engineering tools such as Claude in daily development
Requirements:
4+ years of experience in Data Engineering / Backend Engineering
Strong Python skills
Commercial experience with production LLM integration (OpenAI / Anthropic / Gemini)
Strong knowledge of GCP (Cloud Functions, IAM, Networking)
Experience with BigQuery, Spark, Iceberg
Good understanding of Kubernetes
Experience with workflow orchestration tools (n8n is a strong plus)
Strong practical knowledge of PostgreSQL
English level B2+
What is important for us:
Ownership mindset
Fast learning ability
Strong problem-solving approach
Active AI usage in engineering work
Focus on practical results over unnecessary complexity