Data Engineer, AI Experience

Globaldev Group

Middle Data Engineer with AI experience analyzing business workflows, creating data pipelines, and deploying data solutions. Required Python and data engineering skills with collaboration and communication emphasis.

Posted 5/18/2026full-timeRemote • 🇺🇦 UkraineMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSCloudDockerETLPython

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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.

Benefits

Comp & perks

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.

ATS Keywords

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Hard Skills & Tools

data engineeringdata pipeline developmentETLELTdata transformationdata integrationautomationdata modelingdata qualityobservability

Soft Skills

communicationself-directedproactivecollaborationproduct thinkingflexibility