Hypatos
Your mission
At Hypatos, we build vertical AI Agents that automate document-heavy, back-office workflows across enterprise functions like finance, compliance, procurement, and customer service. To scale our impact, we are looking for a Senior Data Engineer
who will architect and build robust, scalable data infrastructure powering our AI-driven automation systems. This role is deeply technical and cross-functional: You’ll work closely with AI Engineers, Product, and Delivery teams to design distributed data pipelines, optimize real-time data flows, and ensure our systems are reliable, performant, and secure at scale. Key Responsibilities
Design and implement distributed data pipelines using Spark (PySpark), Kafka, and Kubernetes. Build and maintain scalable data infrastructure for real-time and batch processing. Develop and optimize data models and storage solutions using ClickHouse and vector databases. Collaborate with AI engineers to support Retrieval-Augmented Generation (RAG) pipelines and other LLM-powered workflows. Ensure data reliability, performance, and security across all environments. Contribute to CI/CD workflows, testing frameworks, and monitoring solutions for data systems. Translate business requirements into scalable data solutions in collaboration with Product and Delivery teams. Mentor junior engineers and promote best practices in data engineering and distributed systems. Your profile
Attitude : Team player Background : Degree in Computer Science, Software Engineering, or a related discipline (or equivalent professional experience). Experience : 5+ years of experience in data engineering or backend systems, with a strong track record of building production-grade distributed systems. Distributed Systems : Deep understanding of distributed computing patterns and technologies (e.g., Spark, Kafka, Kubernetes). Data Infrastructure :Hands-on experience with ClickHouse, vector databases, and data modeling for high-performance applications. DevOps : Familiarity with CI/CD pipelines, GitHub workflows, Docker, and cloud native environments. AI Integration : Exposure to RAG pipelines and LLM-powered systems is a strong plus. Problem-Solving : Strong analytical mindset with attention to detail, debugging skills, and performance optimization experience. Communication Skills : Ability to clearly articulate technical concepts and collaborate effectively across teams. Growth Mindset : Openness to learning new technologies and adapting to evolving problem spaces. Nice to Have
Experience with Python in production environments. Familiarity with AI/ML-powered products or enterprise automation platforms. Knowledge of cloud platforms (AWS, GCP, or Azure). Experience mentoring or leading engineering teams. Exposure to enterprise system integrations (e.g., SAP, Salesforce, Oracle) Our Promise
We trust
amazing people to do amazing things
and make a long-term impact - we give you Freedom and ownership of meaningful work that directly impacts the business Beyond a top market compensation, you will enjoy a
personal development budget, meal allowance, sporting activities and free beers
as well as a hybrid working model We\'re building a positive organizational culture where
personal and professional
growth are just as important as business growth We believe different perspectives make Hypatos a better community - that is why we\'re committed to building a
diverse and inclusive environment
where you feel you belong
#J-18808-Ljbffr
At Hypatos, we build vertical AI Agents that automate document-heavy, back-office workflows across enterprise functions like finance, compliance, procurement, and customer service. To scale our impact, we are looking for a Senior Data Engineer
who will architect and build robust, scalable data infrastructure powering our AI-driven automation systems. This role is deeply technical and cross-functional: You’ll work closely with AI Engineers, Product, and Delivery teams to design distributed data pipelines, optimize real-time data flows, and ensure our systems are reliable, performant, and secure at scale. Key Responsibilities
Design and implement distributed data pipelines using Spark (PySpark), Kafka, and Kubernetes. Build and maintain scalable data infrastructure for real-time and batch processing. Develop and optimize data models and storage solutions using ClickHouse and vector databases. Collaborate with AI engineers to support Retrieval-Augmented Generation (RAG) pipelines and other LLM-powered workflows. Ensure data reliability, performance, and security across all environments. Contribute to CI/CD workflows, testing frameworks, and monitoring solutions for data systems. Translate business requirements into scalable data solutions in collaboration with Product and Delivery teams. Mentor junior engineers and promote best practices in data engineering and distributed systems. Your profile
Attitude : Team player Background : Degree in Computer Science, Software Engineering, or a related discipline (or equivalent professional experience). Experience : 5+ years of experience in data engineering or backend systems, with a strong track record of building production-grade distributed systems. Distributed Systems : Deep understanding of distributed computing patterns and technologies (e.g., Spark, Kafka, Kubernetes). Data Infrastructure :Hands-on experience with ClickHouse, vector databases, and data modeling for high-performance applications. DevOps : Familiarity with CI/CD pipelines, GitHub workflows, Docker, and cloud native environments. AI Integration : Exposure to RAG pipelines and LLM-powered systems is a strong plus. Problem-Solving : Strong analytical mindset with attention to detail, debugging skills, and performance optimization experience. Communication Skills : Ability to clearly articulate technical concepts and collaborate effectively across teams. Growth Mindset : Openness to learning new technologies and adapting to evolving problem spaces. Nice to Have
Experience with Python in production environments. Familiarity with AI/ML-powered products or enterprise automation platforms. Knowledge of cloud platforms (AWS, GCP, or Azure). Experience mentoring or leading engineering teams. Exposure to enterprise system integrations (e.g., SAP, Salesforce, Oracle) Our Promise
We trust
amazing people to do amazing things
and make a long-term impact - we give you Freedom and ownership of meaningful work that directly impacts the business Beyond a top market compensation, you will enjoy a
personal development budget, meal allowance, sporting activities and free beers
as well as a hybrid working model We\'re building a positive organizational culture where
personal and professional
growth are just as important as business growth We believe different perspectives make Hypatos a better community - that is why we\'re committed to building a
diverse and inclusive environment
where you feel you belong
#J-18808-Ljbffr