Data Engineer (1-year fixed term)

We’re looking for a Data Product Engineer who wants to build modern data and AI foundations that are actually used across the business.

You’ll join our Data Products Team, where we design scalable data platforms, create reliable data products, and develop AI-powered solutions that help teams make faster and smarter decisions. This role goes beyond traditional ETL work: you’ll help shape an AI-ready ecosystem by combining data engineering, automation, semantic modeling, and emerging agentic technologies.

You’ll work on systems that power analytics, self-service BI, operational reporting, machine learning, and AI-driven workflows. From building resilient pipelines and semantic layers to experimenting with AI agents and intelligent automation, your work will directly influence how data is consumed and operationalized across the organization.

We’re looking for someone who enjoys solving complex data problems, improving developer and analyst experience, and exploring practical applications of AI in modern data platforms.

You’ll collaborate closely with data scientists, analytics engineers, BI teams, software engineers, architects, and DevOps in a fast-moving, highly collaborative environment where new ideas and experimentation are encouraged.

Responsibilities

• Create, maintain, and monitor pipelines for regular data processing, leveraging AI-assisted ETL build techniques to ensure data reliability, quality, and efficiency.
• Maintain data serving layer, focusing on designing and implementing an AI-ready semantic layer. 
• Create AI agents to automate repeatable processes and first line of support for end-users.
• Develop integrations with internal and external data sources, defining and enforcing data contracts with clear quality metrics to ensure data integrity.
• Support BI and business in efficient data modeling,  
• Cross-functional cooperation with data scientists, devops, architects, developers, QA and other parties. Collaborate to bring new features and services into production.
• Develop and improve operational practices and procedures