Data Integration Engineer GenAI

Randstad Polska Sp. z o.o.; Kraków; Híbrido; PLN 212.000 - 301.000; Jornada completa

Descripción de la vacante

Randstad Polska Sp. z o.o. is seeking a Data Integration Engineer (GenAI) to design, build, and maintain scalable data integration pipelines and high-performance microservices for Generative AI platforms in a hybrid Kraków environment.

You will leverage Python and FastAPI to connect enterprise stores (Hadoop, Starburst, PostgreSQL, MongoDB) with GCP/BigQuery, and deploy RAG solutions using vector stores like PGVector. Collaboration with AI and data teams is essential.

Formación

• 5-7 years of experience in Data Engineering, Data Integration, or Backend Engineering.
• Strong hands-on Python development experience, including FastAPI and microservices architecture.
• Proven experience building enterprise data pipelines with Big Data engines and data virtualization.
• Solid knowledge of relational and NoSQL databases (PostgreSQL, MongoDB) and hands-on experience with GCP/BigQuery.
• Understanding of Retrieval-Augmented Generation (RAG) architectures and Vector Databases (PGVector).
• Ability to deliver scalable, secure, reliable, and production-ready enterprise data solutions.
• Strong problem-solving, data modeling, and cross-functional collaboration.

Responsabilidades

• Design and develop data integration solutions to support GenAI platforms and applications.
• Build agents that source and retrieve data from multiple enterprise systems for GenAI use cases.
• Develop scalable data transfer pipelines for efficient data movement and processing.
• Design and implement Python-based microservices using FastAPI.
• Integrate structured and unstructured data sources into AI and analytics platforms.
• Build and support RAG solutions and context-aware AI services.
• Develop data access and retrieval services using vector databases and memory stores.
• Work with Cloud platforms including GCP and Azure.
• Design data virtualization and governance solutions for enterprise-scale workloads.
• Collaborate with AI, platform, and data teams to enable GenAI solutions.

Conocimientos

Python

Microservices

Data Integration

Virtualization

Big Data

GCP

GenAI

Vector Stores

Data Modeling

Collaboration

Herramientas

Hadoop

Starburst/Trino

PostgreSQL

MongoDB

Descripción del empleo

We are looking for a Data Integration Engineer (GenAI) to design, build, and maintain scalable data integration pipelines and high-performance microservices for Generative AI platforms. In this role, you will leverage Python and FastAPI to build real-time orchestration services, connect legacy enterprise data stores (Hadoop, Starburst, PostgreSQL, MongoDB) with Google Cloud Platform (GCP / BigQuery), and deploy low-latency Retrieval-Augmented Generation (RAG) solutions using vector stores like PGVector.

If you have a strong background in data engineering or Python backend development, hands-on experience with GCP and vector search, and want to build enterprise-grade AI data retrieval systems in a hybrid Kraków environment, we’d love to talk to you.

What will your tasks involve?

• Design and develop data integration solutions to support Generative AI platforms and applications
• Build agents that source and retrieve data from multiple enterprise systems for GenAI use cases
• Develop scalable data transfer pipelines to enable efficient movement and processing of data
• Design and implement Python based microservices using FastAPI
• Integrate structured and unstructured data sources into AI and analytics platforms
• Build and support Retrieval Augmented Generation RAG solutions and context aware AI services
• Develop data access and retrieval services leveraging vector databases and memory stores
• Work with cloud native services across Google Cloud Platform GCP and Azure
• Design solutions that support data virtualization data governance and enterprise scale AI workloads
• Collaborate with AI engineers platform engineers and data teams to enable GenAI solutions
• Ensure solutions are scalable secure reliable and production ready
• Contribute to evaluation frameworks context engineering and AI model performance improvements

What we expect from you?

• Core Experience: 5-7 years of experience in Data Engineering, Data Integration, or Backend Engineering
• Python & Microservices: Strong hands‑on Python development experience, including FastAPI and microservices architecture
• Data Integration & Virtualization: Proven experience building enterprise data pipelines, with exposure to Big Data engines like Hadoop, Starburst (Trino), and data virtualization
• Databases & Cloud: Solid knowledge of relational and NoSQL databases (PostgreSQL, MongoDB) and hands‑on experience with Google Cloud Platform (GCP & BigQuery)
• GenAI & Vector Stores: Understanding of Retrieval-Augmented Generation (RAG) architectures, Context Engineering, and experience working with Vector Databases (such as PGVector)
• Production Standards: Ability to deliver scalable, secure, reliable, and production-ready enterprise data solutions
• Collaboration: Strong problem-solving, data modeling, and communication skills to collaborate with cross-functional AI, platform, and data teams

What you can expect from us?

• Form of employment: B2B contract
• Hybrid Work Model: Balanced setup with 2-3 days per week in a modern Kraków office and core working hours from 9:00 AM to 5:00 PM CET
• High-Impact Enterprise Environment: Direct involvement in modernizing critical technology ecosystem, combining global banking stability with modern engineering standards
• Cutting-Edge Tech Stack & AI Innovation: Hands-on experience with Python, FastAPI, RAG, PGVector, microservices, and Google Cloud Platform (GCP & BigQuery)
• Global Collaboration & Engineering Culture: Work alongside AI engineers, platform engineers, and international stakeholders within a collaborative, cross-border delivery model

this job offer is intended for people over 18 years of age

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