Data Engineer (ETL/ELT, Cloud/On-Prem, AI Tools)

For our client in the telecommunications sector, we are looking for an experienced Data Engineer who will participate in the design, implementation, and further development of data solutions using modern technologies and artificial intelligence components. The position is suitable for someone with experience in data engineering, data-flow automation, cloud/on-premise data infrastructure, and an interest in using agentic AI to streamline data processes and development.

Key responsibilities: 

• Design, implementation, and automation of data flows (ETL/ELT): data extraction, processing, cleansing, transformation, and visualization.
• Creation and management of data infrastructure in an on-premise or cloud environment.
• Analysis of existing data flows, ETL processes, data lineage, and performing impact analyses.
• Design of data solutions in collaboration with data architects, analysts, and technical teams.
• Delivery of end-to-end data products: datasets, BI reports, API interfaces, and data visualizations.
• Implementation and monitoring of data pipelines, including process automation.
• Collaboration on the use of AI tools to accelerate the development of data solutions and automate ETL processes.
• Preparation of technical documentation, inputs for decision-making processes, and presentation of solutions to stakeholders.
• Coordination of testing, deployment of solutions into production, and post-deployment support.
• Collaboration with data analysts, Data Science teams, and business departments to identify requirements and data sources.
• Participation in improving data processes, optimizing system performance, and resolving incidents.
• Working according to agile or project-based methodologies.

Requirements: 

• At least 4+ years of experience in data engineering.
• Experience with designing, implementing, and managing data flows (ETL/ELT).
• Advanced knowledge of SQL and relational databases.
• Experience with databases such as Oracle, PL/SQL is a strong advantage.
• Experience with data infrastructure in a cloud or on-premise environment.
• Knowledge of data modeling principles, data historization, and the design of scalable data solutions.
• Experience with both batch and real-time data processing.
• Experience with data integrations (API, ETL/ELT, data pipelines).
• Practical knowledge of Python at least at an intermediate level.
• Experience with Unix/Linux environments and scripting.
• Knowledge of BI tools (Power BI, Qlik, Tableau, or similar).
• Experience with CI/CD principles.
• Experience using AI tools in development, ideally:
• agentic AI,
• defining AI skills,
• MCP (Model Context Protocol).
• Ability to navigate project methodologies (Agile, Waterfall).
• Experience coordinating IT projects or technical delivery is an advantage.
• Experience from a telco environment or large enterprise systems.