onsite
Data Engineer - Agentic AI focus
Data Engineer - Agentic AI focus
As a Data Engineer with an Agentic AI focus, you will architect, deploy, and optimize high-performance data ecosystems to transform raw information into actionable intelligence and AI solutions. You will be responsible for designing scalable ETL pipelines, driving AI evolution by integrating LLM frameworks, and ensuring data excellence and integrity for global business intelligence.
About the role
THE ROLE
As a Data Engineer - Agentic AI focus you will architect the high-performance data ecosystem that transforms raw information into actionable intelligence and agentic AI solutions. You will bridge the gap between complex engineering and business impact, collaborating with Data Scientists and Product Managers to build the infrastructure that scales our AI capabilities. This isn't just about moving data; it’s about engineering the foundation for the next generation of automated customer support and operational excellence.
WHAT YOU'LL DO
- Architect Scalable Data Infrastructure: Design, deploy, and optimize production-grade ETL pipelines and data models that ensure high-quality, AI-ready datasets for global business intelligence.
- Drive AI Evolution: Lead the technical preparation and prototyping of AI-driven workflows, integrating emerging LLM frameworks to automate complex business processes and enhance decision-making.
- Ensure Data Excellence and Integrity: Own the end-to-end data management lifecycle, implementing robust governance, security, and monitoring to maintain a "single source of truth" for critical stakeholders.
- Collaborate and Solve Across Functions: Partner with cross-functional teams to translate business needs into technical specifications, serving as the bridge that turns raw data into measurable organizational impact.
- Operational Reliability: Manage business-hour on-call rotations to ensure the seamless performance of ingestion systems, maintaining high availability for our global data consumers.
WHAT YOU BRING
- Advanced Engineering Proficiency: Deep technical expertise in SQL, Python, and data modeling, with a proven track record of maintaining complex data pipelines and workflow orchestration tools like Airflow or DBT.
- Modern Data Stack Expertise: Hands-on experience managing relational and NoSQL environments (such as Snowflake, PostgreSQL, or MongoDB) within AWS cloud infrastructures.
- Growth Mindset & AI Curiosity: A strong desire to apply traditional data engineering principles to intelligent automation, including the ability to adapt to new technologies like LLM orchestration and model evaluation.
- Collaborative Communication: The ability to distill complex technical concepts into clear insights for non-technical partners, ensuring alignment across global time zones and diverse teams.
- We are primarily an in-office environment and therefore, you will be expected to work from the Prague, Czech Republic office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.