AI Data Engineer

Location: Prague, Czechia

Company

hirify.global is expanding its AI and data capabilities through an international team developing data foundations for analytics, machine learning, Generative AI, and LLM applications.

What you will do

• Design, build, and maintain scalable data ingestion, transformation, enrichment, ETL, and ELT pipelines.
• Modernize and migrate legacy data platforms, repositories, databases, file systems, and on-premise environments while preserving data quality and business continuity.
• Develop distributed data solutions with Python, Spark, SQL, and related frameworks.
• Design data architectures for LLM applications, RAG, semantic search, knowledge management, feature stores, training datasets, and inference pipelines.
• Implement metadata, lineage, cataloging, data quality, validation, monitoring, security, and governance solutions.
• Collaborate with Data Engineering, Machine Learning, Data Science, Architecture, Product, and business stakeholders on automation, platform modernization, and AI governance.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
• At least 5 years of experience as a Big Data Engineer or in a similar role, including at least 5 years migrating legacy data platforms, repositories, and operational workflows to modern data architectures.
• Strong proficiency in Scala, Python, or Java, with experience building data solutions using Python, SQL, Spark, and distributed computing frameworks.
• Familiarity with APIs, data integration frameworks, and event-driven architectures.
• Knowledge of data security, encryption, access controls, compliance requirements, data lakes, lakehouses, and data mesh concepts.
• Familiarity with AI and ML workflows, including training data preparation, feature engineering, and model-serving data pipelines.
• Experience with Git, CI/CD pipelines, and infrastructure-as-code practices.
• Strong analytical, problem-solving, communication, stakeholder management, organizational, and prioritization skills, including the ability to manage multiple projects and complex or ambiguous challenges.
• Ability to collaborate across Data Engineering, Data Science, AI, Product, Architecture, and Business teams and to learn new technologies quickly.

Culture & Benefits

• Work in a fast-paced, multicultural, and international environment.
• Participate in agile ceremonies, sprint planning, solution design reviews, architecture discussions, and continuous improvement initiatives.
• Contribute to AI, data innovation, technical debt reduction, automation, and responsible AI initiatives.