EU remote
Senior Data Engineer
About this role
Role: Senior Data Engineer About You: Are you the kind of Data Engineer who enjoys being the person everyone relies on when data matters most? Do you thrive on building reliable pipelines, improving data quality and ensuring critical business decisions are driven by trusted information? Are you as comfortable writing complex SQL as you are building automated monitoring, troubleshooting failures and improving data architecture? If you enjoy ownership and want to have a direct impact on how a fast-growing business operates, DFYNE could be exactly where you belong.
About DFYNE: A picture paints a thousand words… and we’re sure you don’t want to sit here reading a corporate essay about who we are. Honestly, how can you really get under the skin of DFYNE from a few lines on a screen? So instead, go have a look for yourself, see what we’re about, what we stand for, and why people love us: www.dfyne.com . About the role — DFYNE Your Career: Before I tell you more about the role, let me introduce myself.
I’m Bruce, Head of Development at DFYNE, and I’m looking for our first dedicated Senior Data Engineer. This role will own the DFYNE data warehouse, helping ensure the data that powers finance reporting, forecasting, inventory management and operational decision-making remains accurate, reliable and available. You’ll take ownership of BigQuery pipelines, transformation layers, exports and integrations while working closely with teams across the business.
This is a hands-on role where you’ll help define data engineering standards, improve data reliability and build the foundation of DFYNE’s future data capability. Attitude: • Ownership mentality • Builder mindset • Commercial awareness • Problem-solving mindset • Continuous improvement Key Responsibilities: • Own the performance, reliability, security and ongoing development of DFYNE’s BigQuery data warehouse and associated data pipelines.
• Design, build and maintain scalable ingestion and transformation processes. • Implement data quality monitoring, validation and automated alerting. • Define data contracts with business stakeholders and system owners. • Improve reliability, accuracy and freshness of business-critical data. • Lead investigation and resolution of data incidents, ensuring root causes are identified and permanently addressed. • Support ERP, finance, forecasting and operational reporting requirements.