Data Engineer (AI)

TL;DR

Data Engineer (AI): Building scalable data pipelines and governed data products for AI-ready platforms with an accent on medallion architecture, data quality, and governance. Focus on desihirify.globaling datasets for analytics and AI use cases including LLM grounding and RAG solutions.

Location: Warsaw. Flexible working conditions – hybrid work model or remote work from Poland.

Company

hirify.global brings people closer through leading intelligent hearing, audio, video, and gaming solutions.

What you will do

• Build and maintain scalable data pipelines (batch and near real-time)
• Desihirify.global and implement medallion architecture (Bronze / Silver / Gold)
• Develop data products with schema validation, versioning, and governance standards
• Prepare datasets for analytics and AI use cases (including LLM grounding and RAG)
• Ensure data quality, monitoring, and observability
• Implement data governance (classification, ownership, lineage)
• Support embedding and retrieval pipelines for AI solutions
• Contribute to CI/CD pipelines for data platform deployments

Requirements

• 3–7 years of experience in Data Engineering
• Strong skills in Python, SQL, PySpark
• Experience with ETL/ELT pipelines and data modeling
• Knowledge of distributed data processing systems
• Experience with Azure or equivalent cloud platforms
• Familiarity with lakehouse architectures (Databricks, Microsoft Fabric, Synapse)
• Understanding of data governance (PII, metadata, lineage)
• Experience with Git and CI/CD (Azure DevOps or GitHub Actions)

Nice to have

• Exposure to LLM / embeddings / RAG concepts
• Experience with vector search or Azure AI Search
• Knowledge of Semantic Kernel or LangChain
• Experience with streaming / event-driven pipelines
• API-based data ingestion experience

Culture & Benefits

• Competitive pay with annual bonus
• Attractive benefits package including medical care, lunch/cafeteria card, life insurance and pension plan
• Opportunity to work with multiple stakeholders and receive strong professional support
• Environment that enables knowledge sharing and best practice exchange
• Ongoing development opportunities in a multinational environment
• Varied tasks and projects with clear ownership and impact