Data Engineer - Agentic AI focus

Pure Storage

Prague, Czech Republic

Full Time

Posted May 6, 2026

Not Specified

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Job Description

A Data Engineer focusing on Agentic AI is responsible for designing and maintaining scalable data infrastructure, integrating AI frameworks, and collaborating with cross-functional teams to enable advanced AI-driven automation and insights within a data storage and processing environment.

Key Responsibilities

Design, deploy, and optimize scalable ETL pipelines and data models for AI-ready datasets.
Lead the development and prototyping of AI-driven workflows, integrating emerging LLM frameworks.
Manage end-to-end data lifecycle, ensuring data governance, security, and integrity.
Collaborate with cross-functional teams to translate business needs into technical data solutions.
Maintain high availability and performance of data ingestion systems through on-call rotations.

Requirements

Proven technical expertise in SQL, Python, and data modeling, with experience maintaining complex data pipelines and workflow orchestration tools like Airflow or DBT.
Hands-on experience managing relational and NoSQL environments such as Snowflake, PostgreSQL, or MongoDB within AWS cloud infrastructures.
Deep technical proficiency in designing, deploying, and optimizing production-grade ETL pipelines and data models to ensure high-quality, AI-ready datasets.
Experience leading the technical preparation and prototyping of AI-driven workflows, integrating emerging LLM frameworks to automate complex business processes and enhance decision-making.
Ownership of the end-to-end data management lifecycle, including implementing robust governance, security, and monitoring to maintain a single source of truth for critical stakeholders.
Ability to collaborate with cross-functional teams to translate business needs into technical specifications and turn raw data into measurable organizational impact.
Experience managing business-hour on-call rotations to ensure the seamless performance and high availability of ingestion systems for global data consumers.
Advanced engineering proficiency in SQL, Python, and data modeling, with a proven track record of maintaining complex data pipelines and workflow orchestration tools.
Hands-on experience managing relational and NoSQL environments such as Snowflake, PostgreSQL, or MongoDB within AWS cloud infrastructures.
Strong desire and curiosity to apply traditional data engineering principles to intelligent automation, including adapting to new technologies like LLM orchestration and model evaluation.
Ability to distill complex technical concepts into clear insights for non-technical partners and ensure alignment across global teams.
Willingness to work primarily from the Prague, Czech Republic office in accordance with company policies, unless on PTO, work travel, or other approved leave.