Developing and driving the architecture of complex data systems that prioritize scalability, reliability, and long-term maintainability.
Designing and optimizing production-grade data pipelines, with a primary focus on high-throughput, real-time streaming.
Driving Spec-Driven Development (SDD) using OpenSpec or GitHub Spec Kit to create strict engineering contracts that ensure predictable, high-quality AI code generation.
Orchestrating agentic AI workflows with Claude Code and the Model Context Protocol (MCP) to rapidly build, refactor, and scale our data infrastructure.
Taking full accountability and ownership of system components, working in a self-sufficient manner to solve deep technical challenges.
Implementing rigorous testing and monitoring frameworks to ensure the integrity of mission-critical data.
Mentoring junior engineers and fostering a culture of technical excellence through open feedback and architectural reviews
Requirements
10+ years of professional experience, with 5+ years specifically focused on Data Engineering.
Deep technical expertise with Kafka (including Producers, Consumers, and Stream Processing) for building scalable, real-time architectures.
Strong experience with OLAP databases (expertise in Clickhouse is highly preferred).
Good fluency in Python and SQL for complex data manipulation, optimization, and system building.
Willingness to embrace highly agentic AI-assisted development, specifically using Claude Code to autonomously navigate codebases, execute multi-step engineering tasks, and accelerate development cycles while maintaining high code quality.
Strong hands-on experience with Docker, Kubernetes, and automated CI/CD pipelines.
Significant experience with open-source tools and technologies within the modern data stack.
Excellent communication skills and a desire to work in an environment based on transparency and feedback.
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