Middle Data Engineer + AI experience at Globaldev Group
, , Poland -
Full Time


Start Date

Immediate

Expiry Date

16 Aug, 26

Salary

0.0

Posted On

18 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, Airflow, Dbt, Redshift, ETL/ELT, LLM, RAG, Prompt Engineering, LangChain, LlamaIndex, Docker, CI/CD, AWS, Data Modeling, Backend Integration, Frontend Development

Industry

IT Services and IT Consulting

Description
Requirements 3+ years of experience in Data Engineering Strong data engineering background with the ability to design and own solutions end-to-end Proficiency in Python, Airflow, dbt, and Redshift for data processing, pipeline development, and transformation Experience building and maintaining ETL / ELT pipelines and data integrations, including fetching and normalizing data from non-robust 3rd party sources Hands-on experience with LLM/agent-based automation applied to business processes (e.g., building agents or LLM-powered workflows for data transformation, testing, or extraction) Practical familiarity with modern AI tooling — LLM APIs (OpenAI, Anthropic, etc.), RAG patterns, prompt engineering, and agent frameworks (LangChain, LlamaIndex, or similar) Cross-functional flexibility: comfortable stepping beyond pure DE work into adjacent areas — light DevOps (Docker, CI/CD, cloud deployment), backend integration, and basic frontend when a POC requires it Excellent communication skills — able to explain technical decisions to non-technical stakeholders Self-directed and proactive: able to spot workflow inefficiencies and drive improvements with minimal supervision Product thinking: collaborate with business teams, propose solution approaches, build quick POCs, iterate on feedback, and support production deployment Responsibilities Analyze business workflows and identify opportunities for data automation and AI-driven process automation Design, build, and maintain scalable data pipelines and integrations, including ingestion from unreliable or unstructured 3rd party sources Build LLM- and agent-based solutions for data transformation, validation/testing, and extraction tasks Containerize data and AI workloads using Docker and deploy to cloud infrastructure (AWS) Develop prototypes and POCs to validate ideas quickly — both data pipelines and AI-powered workflows Collaborate with business and technical teams to refine requirements and iterate on solutions Support the deployment and integration of data and AI solutions into production systems Continuously improve data processes through automation and AI-driven approaches Contribute to data modeling, quality, and observability practices What we offer Direct cooperation with the already successful, long-term, and growing project. Flexible work arrangements. Collaborative and supportive team culture. Truly competitive salary. Help and support from our caring HR team.

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Responsibilities
Design and maintain scalable data pipelines and integrations, focusing on ingestion from unstructured third-party sources. Develop and deploy LLM- and agent-based automation solutions to optimize business processes and data transformation.
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