Middle Data Engineer + AI experience

About Globaldev: Globaldev is a high-performing technology transformation partner dedicated to crafting custom software ecosystems, scalable data infrastructures, and cutting-edge artificial intelligence models. Collaborating directly with successful, long-term international projects, we foster a product-focused engineering environment that empowers developers to build innovative solutions from scratch.

Role Summary

We are seeking a proactive Middle Data Engineer with hands-on AI experience to design, own, and optimize our data transformation layers end-to-end. In this high-agency role, you will bridge the gap between traditional data warehouse engineering and generative AI workflows. You will design automated ETL/ELT pipelines while building LLM agent-based solutions for text extraction, testing automation, and non-robust 3rd party data integrations. This position is perfect for engineers who comfortably slide into adjacent light-DevOps tasks and fast prototyping loops to bring POCs to life.

Key Responsibilities

• Pipeline Architecture & Automation: Design, build, and maintain scalable ETL/ELT data pipelines. Fetch, normalize, and clean raw data payloads streaming from erratic, unstructured third-party API endpoints.
• AI & Agentic Systems Implementation: Deploy functional AI solutions leveraging native LLM APIs, prompt engineering methodologies, and advanced Retrieval-Augmented Generation (RAG) structures to automate core business workflows.
• Data Transformation Logic: Own data modeling, schema optimization, and transformation layer configurations utilizing Python, Apache Airflow, dbt, and Amazon Redshift.
• Prototyping & Agile Feedback: Collaborate directly with business product squads to identify workflow inefficiencies, build rapid proof-of-concepts (POCs), iterate based on stakeholder feedback, and support production deployment loops.
• Cross-Functional Operations: Containerize data engineering and AI workloads using Docker, managing light DevOps tasks, CI/CD integrations, and basic cloud deployments on AWS.
• Observability & Governance: Maximize data quality, pipeline monitoring instrumentation, and structural data observability metrics across the enterprise infrastructure layer.

Required Skills & Qualifications

• 3+ years of professional hands-on experience in Data Engineering, Infrastructure Analytics, or core Backend pipeline development.
• Deep proficiency building automated data manipulation systems using Python, Apache Airflow, dbt, and Amazon Redshift.
• Practical exposure building and deploying LLM orchestration or agentic workflows using frameworks like LangChain or LlamaIndex.
• Familiarity interacting with modern generative AI endpoint APIs (OpenAI, Anthropic, etc.) and implementing structured RAG search routing patterns.
• Hands-on familiarity with containerization tools—specifically **Docker**—alongside basic cloud deployment infrastructure on AWS.
• Self-directed, proactive operator with strong problem-solving skills and the ability to explain complex technical transformations easily to non-technical stakeholders.
• Location Context: 100% remote working flexibility open to qualified software engineers operating from Ukraine or Poland.

What We Offer

• Direct cooperation with a highly successful, long-term, and growing international tech project.
• Truly competitive benchmarked salary package.
• Highly flexible working arrangements and autonomy over your technical solutions footprint.
• A supportive, collaborative team culture backed by a dedicated and caring HR support team.