AI Data Engineer

Quick Facts

• Focus: designing and building data pipelines for AI solutions
• Tech stack: Python (PySpark), SQL, Databricks, REST API, ETL/ELT

Description

Design and develop processes for acquiring, processing, and sharing data for AI-based solutions. Build Python (PySpark) components that integrate data with LLMs, AI agents, and business systems in a Databricks environment, including ETL/ELT, REST API integration, validation, quality, security, and monitoring. Work with AI Engineers, Data Scientists, architects, and business experts in a Scrum team, with code reviews and test automation.

Responsibilities

• Design and develop data acquisition, processing, and publishing processes for AI solutions
• Build PySpark components integrating data with language models, AI agents, and business systems in Databricks
• Process structured data and content from messages, documents, and attachments
• Create ETL/ELT processes, integrate REST APIs, and implement data validation mechanisms
• Ensure data quality, consistency, security, and monitoring
• Write automated tests, analyze errors, and improve exception handling
• Collaborate with AI/Data/engineering and business roles; participate in architecture design, code review, and Scrum work

Requirements

• Minimum 3 years of experience as a Data Engineer, Python Developer, or similar role
• Very good knowledge of Python and SQL
• Experience building ETL/ELT processes and integrating data from multiple sources
• Experience designing and using REST APIs
• Ability to work with structured and unstructured data
• Knowledge of Git, CI/CD, automated testing, and software best practices
• Experience with applications using LLMs
• Communicative English

Benefits

• Challenging projects and collaboration with experienced IT professionals
• Access to the latest technologies
• Interesting projects
• Values-driven culture: community, simplicity, client at the center, responsibility, credibility
• Stable enterprise environment