Senior Data Engineer

Location: Bulgaria, Czechia, Hungary, Moldova, Romania, or Slovakia; work from the European Union region and a valid work permit are required.

Company

Global AI-first digital transformation and engineering partner delivering scalable products, platforms, data solutions, and AI solutions across 16 countries.

What you will do

• Design and build consumable data assets and data products on an AWS data platform, including schemas, documentation, ownership, and handover to product teams.
• Work with product engineering teams to define data contracts, map domain ownership, and connect data to the wider platform landscape.
• Onboard bronze- and silver-layer data from legacy warehouses using internal agentic tooling.
• Build streaming and batch pipelines and tooling with Flink, SQL, Python, Kafka, Iceberg, DynamoDB, and AWS services.
• Support teams with pipeline and batch-job debugging while promoting engineering best practices through pairing, reviews, and practical guidance.
• Own technical initiatives from planning through successful completion and help teams adopt data ownership.

Requirements

• Strong data engineering experience with large-scale data platforms and big data workloads.
• Hands-on experience with stream processing, event-driven architecture, schema management, and batch data engineering.
• Practical experience with AWS, Kafka, Iceberg, DynamoDB, and core AWS services; exposure to Apache Flink with SQL or Python.
• Experience at Lead Engineer level, including setting technical direction, delivering work end to end, and owning outcomes.
• Strong stakeholder management, communication, and cross-team collaboration skills.
• Fluent English in written and spoken communication; work from the European Union region and a valid work permit are required.

Nice to have

• Experience with data mesh concepts, data products, data contracts, domain ownership, and federated governance.
• Experience with AI-assisted engineering, agentic tooling, or structured GenAI workflows in the software development lifecycle.
• Awareness of Kubernetes and experience in data platform enablement or internal developer experience.
• Background in high-volume operational or transactional environments where data volume and latency are important.

Culture & Benefits

• Work in a lean, fast-moving platform team of approximately six engineers with a part-time Product Manager.
• Collaborate closely with product engineering teams and platform users through pairing, reviews, and hands-on guidance.
• Contribute to a people-first engineering culture focused on knowledge sharing and continuous growth.
• Use modern cloud, data, and AI technologies across client engineering projects.

Hiring process

• CV review.
• HR call, interview, and client interview.
• Final decision.