ABOUT EUROWINGS DIGITAL

ABOUT THE JOB

As Staff Data Engineer (all genders), you will shape and scale our cloud data platform and its reference architecture. Your mission is to enable trusted, well governed data products for analytics, reporting, and advanced use cases by setting technical direction, establishing engineering standards, and leading delivery in complex cross-team environments.

You will work hands on across the end-to-end data product lifecycle, from translating domain needs into clear contracts and scalable models, to building and evolving ingestion and transformation patterns, to ensuring discoverability, lineage, access controls, and quality monitoring. You combine deep data engineering expertise with strong software engineering practices. You care about reliability, security, and operational excellence, and mentor others to raise the bar across the organization.

WHAT YOU'LL DO

• Design and evolve scalable data products architectures that support analytics, reporting, and advanced use cases across domains
• Partner with domain and product teams to translate business needs into clear data product contracts aligned with our data platform architecture and strategy
• Build and operate reliable ingestion and transformation pipelines, with strong testing, observability,and cost aware operations
• Lead delivery and technical alignment n complex cross team initiatives through design reviews, mentoring, and hands on contribution
• Collaborate closely with platform,security,and operations stakeholders to align engineering standards, CI/CD, and best practices
• Work in an agile environment using Scrum or Kanban, contributing to planning, prioritization, and continuous improvement

WHAT YOU'LL NEED

• 5+ years in data engineering or data architecture roles in cloud environment (preferably Microsoft Azure), including designing scalable lakehouse platforms and reference architectures
• Strong SQL skills plus hands on experience with Databricks and Apache Spark, including performance tuning and cost aware design on Azure
• Proven experience budling production grade ingestion and transformation pipelines, ideally with Delta Lake patterns,orchestration, and robust testing
• Solid software engineering practices for data systems,including Python or Scala, Git based workflows,CI/CD, and infrastructure as code such as Terraform
• Experience with modern data governance and security, including Unity Catalog concepts, RBAC, ABAC, data masking, lineage, and auditing
• Strong data modeling capability for analytics and data products, including dimensional and domain-oriented modeling, plus designing data products, SLAs, and data quality controls

WHAT YOU'LL BRING

• Structured, analytical thinking with a bias for pragmatic, scalable design and long-term maintainability of a lakehouse platform and its data products
• Product mindset for data platforms, focusing on reusable patterns, accelerators and standards that speed up delivery for multiple teams
• Strong problem solving and stakeholder translation skills, turning ambiguous domain needs into clear technical direction, roadmaps, and delivery guidance
• Ownership for DataOps and operational excellence, including testing, observability, incident learnings, and cost efficient runtime practices
• Strong collaboration skills to build governance by design, partnering closely with data governance stakeholders on processes, access controls, and data product readiness
• Communication and mentoring strength, influencing through design reviews, hands on contribution, and raising engineering quality across the organization
• Curiosity and learning mindset, with interest in enabling ML and AI use cases by strengthening platform foundations and consistent data product delivery