• Build and optimize real-time streaming pipelines to ensure efficient routing of voice and chat session data into enterprise data platforms • Integrate generative AI solutions with enterprise knowledge bases to ensure accurate and context-aware conversational agent performance • Maintain and configure low-latency databases to ensure secure and reliable storage of session states and operational metadata • Design system architectures and technical blueprints to ensure scalable, resilient, and high-performance solutions • Delegate and manage engineering tasks to ensure effective team productivity and capability development • Develop and execute testing processes to identify system issues and ensure quality and stability in deployed solutions • Collaborate with stakeholders to align requirements, manage expectations, and ensure successful project delivery • Oversee automated PII redaction workflows across voice and text streams to ensure full compliance with data privacy requirements prior to storage.

Role Description - Aufbau, Betrieb und Weiterentwicklung einer skalierbaren Datenplattform (Warehouse / Lake / Lakehouse) - Entwicklung und Wartung robuster ETL/ELT-Pipelines zur Integration unterschiedlichster Datenquellen - Sicherstellung von Datenqualität, Performance, Skalierbarkeit und Kostenoptimierung - Implementierung von Monitoring-, Governance- und Sicherheitskonzepten (inkl. DSGVO) - Enge Zusammenarbeit mit Analytics-, Product- und Engineering-Teams - Automatisierung von Datenprozessen sowie kontinuierliche Verbesserung bestehender Architekturen - Aktive Mitgestaltung der Datenstrategie und Evaluation neuer Technologien Qualifications - Mehrjährige Erfahrung im Data Engineering oder in einer vergleichbaren Rolle - Sehr gute Programmierkenntnisse in Python und SQL sowie saubere Engineering-Standards (Tests, CI/CD) - Fundiertes Verständnis moderner Datenarchitekturen und Datenmodellierung - Praxiserfahrung mit Cloud-Plattformen (AWS, GCP oder Azure) und gängigen Data-Tools (z. B. Airflow, dbt, Spark, Snowflake) - Hohes Qualitäts- und Ownership-Mindset für produktive Datenpipelines - Fähigkeit, technische Lösungen verständlich zu kommunizieren und Business-Anforderungen zu übersetzen - Teamplayer mit Interesse an Mentoring und kontinuierlicher Weiterentwicklung - Verhandlungssichere Englischkenntnisse (erforderlich); Deutschkenntnisse sind ein Plus Benefits - Attraktive, marktgerechte Vergütung - Flexibles Arbeitsmodell: Remote-first mit optionaler Präsenz im Büro - 30 Urlaubstage - Strukturiertes Onboarding mit persönlicher Begleitung durch das Recruiting-Team - Transparente Kommunikation durch wöchentliche 1:1s und regelmäßige All-Hands-Meetings - Zugang zu Corporate Benefits - Langfristige Perspektive in einer wachsenden Unternehmensgruppe

Role Description This is a Staff-level role in title and in scope, but it's not a role where you'll be directing traffic from a distance. You'll be the only Data Engineer in our ANZ team (for now), which means you're setting the architectural direction and doing the hands-on work. Warehouse infrastructure, ETL and reverse ETL, pipeline builds, fact table design, data dictionary governance, that's all you. The organisational influence is real, but so is the technical execution. The decisions you make here will be ones that engineers, analysts, and clinical teams depend on for a long time. So will the standards you set. This isn't a role where you'll be handed a finished data function to run, you'll be shaping what it becomes, and building a lot of it yourself. What You'll Be Doing: - Defining the architectural patterns, modelling standards, and pipeline conventions that teams across the organisation build on and building them yourself. - Owning the warehouse infrastructure, ETL and reverse ETL processes, authoritative fact tables, and data dictionary governance end-to-end. - Leading the most strategically significant data initiatives in your area and dealing with the blockers, unclear priorities, dependency gaps and quality failures that get in the way. - Working closely with senior stakeholders in product, clinical, and technology to make sure data is part of the conversation early, not bolted on after. - Owning data quality across your domain, auditing gaps, surfacing inconsistencies across markets, and driving the remediation work. - Developing the analysts and junior engineers around you, including the harder conversations about growth and direction. - Helping senior leadership understand what the data function can and can't reliably deliver, so investment decisions are grounded in reality. Qualifications - 10+ years in data engineering, with experience setting technical direction and still being the person who builds it. - Deep hands-on expertise with BigQuery, dbt or equivalent, and AWS. - Comfortable being the most senior data engineering voice in the room while still being deeply in the weeds day-to-day. - A track record of making architectural decisions others have depended on. - Experience working with senior stakeholders and bringing a commercial perspective to data decisions. - Someone who takes developing people as seriously as the technical work. Requirements - Nice to have: Healthcare or regulated industry experience. - Experience scaling a data function through a growth period. - Data observability, data contracts, or governance at scale. Benefits - Work From Anywhere. 🌍 - A competitive salary and awesome benefits package. 💰 - A supportive and positive work environment. 🌟 - Opportunities to grow and develop your career. 📈 - Opportunity to transform lives through alternative medicine. 💡

Role Description Our data function is growing and we're looking for a Senior Data Engineer to take real ownership of the back-end, the warehouse, pipelines, ETL and reverse ETL, fact tables, and the data dictionary that keeps everything consistent. You won't be handed a pristine setup. There are gaps, there's multi-market complexity, and there's real work to do. You'll be the person who designs the architecture that others build on, and you'll have the scope to shape how data engineering is practised here, the standards, the tooling choices, the modelling patterns. If you want to own something meaningful rather than maintain someone else's decisions, this is worth a look. What You'll Be Doing: - Designing and implementing data architecture for new capability areas - modelling approaches in dbt, pipeline reliability decisions, the works. - Owning our ETL and reverse ETL processes, warehouse structure, authoritative fact tables, and data dictionary definitions. - Finding and fixing data quality and coverage gaps across markets, and building the monitoring infrastructure to catch them earlier next time. - Leading data initiatives end-to-end across Product, Analytics, and Clinical teams - managing competing priorities without losing momentum. - Presenting your work and decisions to senior stakeholders, and being comfortable pushing back when the data doesn't support what's being assumed. - Working with our analysts and engineers and gradually lifting the standard of how the team works. Qualifications - 6+ years in Data Engineering with genuine end-to-end ownership, pipelines, warehouse, the lot. - Solid experience with BigQuery, dbt or equivalent, and AWS. - Someone who can deliver under ambiguity and doesn't need a perfect brief to get started. - Good communication, you'll be talking to non-technical stakeholders regularly and need to make it land. Requirements - Healthcare or regulated industry experience. - Reverse ETL tooling or data observability experience. - Experience designing A/B tests or pilots before the fact, not after. Benefits - Work From Anywhere. 🌍 - A competitive salary and awesome benefits package. 💰 - A supportive and positive work environment. 🌟 - Opportunities to grow and develop your career. 📈 - Opportunity to transform lives through alternative medicine. 💡