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Job Description
A Data AI Engineer responsible for designing and maintaining scalable data infrastructure, developing AI-driven workflows, and ensuring data quality to support advanced AI applications and business intelligence initiatives.
Key Responsibilities
- Architect, design, deploy, and optimize high-performance data ecosystems and ETL pipelines for AI-ready datasets.
- Lead the development and prototyping of AI-driven workflows, integrating emerging LLM frameworks to automate business processes.
- Manage end-to-end data lifecycle, ensuring data governance, security, and integrity for reliable organizational insights.
- Collaborate with cross-functional teams to translate business needs into technical data solutions.
- Maintain system performance and high availability through on-call rotations and operational monitoring.
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 database 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 that ensure high-quality, AI-ready datasets for global business intelligence.
- 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, effectively turning 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.
- Strong desire and ability to apply traditional data engineering principles to intelligent automation, including adapting to new technologies like LLM orchestration and model evaluation.
- Excellent communication skills 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 compliance with company policies, unless on PTO, work travel, or other approved leave.
Benefits & Perks
Flexible time off
Wellness resources
Company-sponsored team events
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