Senior Software Engineer - Eagle Eye

Description

The company is a global healthcare technology business with more than 95,000 employees across over 150 countries, building medical technology used by more than 72 million patients a year.

The Eagle Eye team sits within Patient Care Systems (PCS), which builds the connected platform clinicians use to monitor and manage patients with implantable cardiac devices.

The team turns field data from the company's device logs into insight. It runs two areas: an Elastic-based data platform that ingests, processes and monitors device logs, and Field Investigations, which uses that data to find the root cause of field complaints and issues.

You will work with R&D, software engineering quality, complaint handling and field partners in the US and Ireland. The work produces reliable, validated data tools and clear, evidence-based investigation results inside a regulated medical device environment.

This is a senior role on a hybrid basis.

Responsibilities

• Build and maintain Python data-processing services on Azure Functions that ingest, parse and analyze device logs at scale.
• Build and maintain Elastic Stack content on Elastic Cloud, including ingest pipelines, Elastic Common Schema mappings, data streams, lifecycle policies and transforms.
• Run and evolve the Elastic Cloud platform, covering version upgrades, capacity and scaling, security roles and infrastructure as code.
• Create Kibana dashboards, alerting rules and monitoring that show data health, ingestion delay and issue trends.
• Investigate field complaints by analyzing device logs, implant session data and device information to find root cause.
• Write clear investigation summaries and reports that support complaint handling, CAPAs, health hazard evaluations and FDA summary reporting.
• Automate recurring investigations with Python scripts and issue detection rules so problems are caught earlier and more consistently.
• Release and deploy team tools through Azure DevOps pipelines and Octopus Deploy, and complete the method validation and documentation a regulated environment requires.
• Work with R&D, quality, complaint handling and field teams to turn their questions into data, tools and answers.
• Mentor and coach engineers in a collaborative, learning-focused team.
• Help shape technical decisions on data platform design, data quality, investigation tooling and engineering practices.
• Work with complaint handling, quality and R&D stakeholders to understand the questions behind their requests and build practical, maintainable data solutions.
• Separate signal from noise, and explain findings and how confident you are in them to both technical and non-technical audiences.
• Give technical guidance to peers, dashboard and tool users, and project partners.
• Collaborate with engineering, quality and leadership across a matrixed organization.
• Design pipelines that scale with growing data volumes while protecting accuracy, completeness and timeliness.
• Change schemas, tools and dashboards without breaking downstream users, reports and integrations, and provide migration paths when changes are needed.
• Diagnose performance, memory and reliability problems in data processing and trace them to root cause with measurable results.
• Apply software architecture and design principles to build reliable, maintainable data services and tools.
• Use AI tools and agents for code, data analysis, investigation summaries and troubleshooting, and check their outputs carefully.

Requirements

• A bachelor's degree in Computer Engineering, Software Engineering, Computer Science, Electrical Engineering or a related technical field.
• At least 4 years of software engineering experience.
• Substantial professional experience designing, developing, debugging and maintaining software through the full lifecycle, using Python or a comparable language.
• Experience building data pipelines or analytics on large volumes of log or event data.
• Preferred: familiarity with the Elastic Stack (Elasticsearch, Kibana, ingest pipelines, transforms), ideally on Elastic Cloud.
• Preferred: experience with Elasticsearch query and scripting languages, including Query DSL, ES|QL, Kibana Query Language (KQL) and Painless.
• Preferred: experience with Microsoft Azure, including Azure Functions and Azure Monitor or Application Insights (Kusto Query Language).
• Preferred: experience with CI/CD and releases using Azure Pipelines, Octopus Deploy and SonarQube.
• Preferred: experience with infrastructure as code using Terraform.
• Preferred: experience investigating field software issues and performing root cause analysis from logs and diagnostic data.
• Preferred: familiarity with complaint handling, CAPA, post-market surveillance processes and TrackWise.
• Preferred: experience validating software tools used in regulated processes.
• Preferred: experience applying AI or large language models to data analysis or reporting.
• Preferred: familiarity with regulated product development and standards such as ISO 13485, IEC 62304, ISO 14971 and 21 CFR 820.
• Preferred: experience with Agile methodologies.
• Preferred: experience using Azure DevOps and/or GitHub.
• Preferred: strong collaboration, communication and technical documentation skills.

Conditions

Hybrid work arrangement.

Ireland pay range: 65,600.00 EUR to 98,400.00 EUR.

The final salary within this range depends on objective, job-related criteria such as relevant experience, skills and qualifications, under the company's compensation framework.

The statements describe the general nature and level of the role and are not a full list of every responsibility and skill.

Benefits

• A competitive salary and a flexible benefits package.
• A wide range of benefits, resources and competitive pay plans designed to support you at every career and life stage.
• The role is eligible for a short-term incentive called the MIP, the company's incentive plan.