Auditdata

Support Engineer

• Provide expert technical support for audiometers and hearing diagnostic equipment
• Troubleshoot and diagnose hardware, connectivity, and system integration issues involving audiometers, PCs, and clinical software
• Guide customers through installation, configuration, and setup of audiology systems
• Support clinics and partners during deployment, upgrades, and operational troubleshooting
• Investigate and reproduce customer-reported issues to determine root cause, develop targeted troubleshooting steps, and classify failures by domain — software, hardware, firmware, or transducer — before escalating to the appropriate team.
• Maintain full technical mastery across all audiometer domains — software, hardware, firmware, and transducers — to independently diagnose and resolve issues at every level
• Work closely with engineering and product teams, escalating confirmed root causes via structured defect reports covering software/firmware versions, hardware data, and transducer specs
• Document troubleshooting procedures and use AI tools to maintain the knowledge base, converting resolved cases into searchable articles and guided troubleshooting flows
• Provide remote technical support via phone, email, and remote diagnostic tools
• Assist with testing of new instrument integrations, firmware updates, and product releases
• Ensure timely resolution of customer cases according to service level agreements (SLAs)

Technical Support Engineer, L2/L3

Business Intelligence Developer

• Own the analytical layer that transforms clinical and operational data into clear, actionable insights for our customers.
• Design and build reporting solutions on top of our modern Microsoft Fabric data platform.
• Collaborate with product, clinical, and engineering stakeholders to ensure data accuracy and compelling storytelling.
• Design and develop customer-facing reports and dashboards, focusing on clarity, performance, and clinical relevance.
• Build and maintain analytical data models on Microsoft Fabric, including star schemas, KPI definitions, and DAX measures.
• Own data quality — define expectations, detect anomalies, and resolve issues at the source.
• Develop and maintain ETL/ELT pipelines integrating data from multiple sources.
• Write Python scripts for automation or data transformation logic.

BI Engineer

Backend Engineer

• Lead a small remote scrum team (typically 3–6 engineers): planning, execution, coaching, and delivery.
• Stay hands-on in C#/.NET: design and implement backend services, review PRs, and keep architecture pragmatic.
• Ship AI-enabled features to production by integrating AI components (e.g., speech-to-text and LLM services) into our workflows and microservice ecosystem.
• Make delivery predictable: break down work into milestones, manage dependencies with other teams, and keep releases on track.
• Set the quality bar: testing discipline, CI/CD, observability, performance, reliability, and secure engineering practices.
• Partner with Product and stakeholders: to clarify requirements, communicate trade-offs (quality vs. latency vs. cost), and ensure what ships works in real clinical workflows.

Technical Support Engineer, L2/L3

BI Engineer

Team Lead – AI Services, .NET