Lead Engineer, Data Engineering

Resmed • San Diego, CA

5h • $171,000 - $257,000 • Hybrid

About The Position

Global Technology Solutions (GTS) at ResMed is a division dedicated to creating innovative, scalable, and secure platforms and services for patients, providers, and people across ResMed. The primary goal of GTS is to accelerate well-being and growth by transforming the core, enabling patient, people, and partner outcomes, and building future-ready operations. The strategy of GTS focuses on aligning goals and promoting collaboration across all organizational areas. This includes fostering shared ownership, developing flexible platforms that can easily scale to meet global demands, and implementing global standards for key processes to ensure efficiency and consistency. Global Technology Solutions (GTS) at ResMed is a division dedicated to creating innovative, scalable, and secure platforms and services for patients, providers, and people across ResMed. The primary goal of GTS is to accelerate well-being and growth by transforming the core, enabling patient, people, and partner outcomes, and building future-ready operations. The strategy of GTS focuses on aligning goals and promoting collaboration across all organizational areas. This includes fostering shared ownership, developing flexible platforms that can easily scale to meet global demands, and implementing global standards for key processes to ensure efficiency and consistency. Lead Engineer (Data Engineering) Hybrid – San Diego (1 day/week onsite) At Resmed , we don’t just build technology, we create solutions that transform lives. As a global leader in connected devices and digital health, we empower millions of people worldwide to sleep, breathe, and live better lives. We are looking for a high-impact, hands-on Lead Engineer to shape the next generation of ResMed’s data ecosystem. This is a Senior Staff–level technical leadership role for someone who can set direction, define patterns, solve complex architectural challenges, and elevate our data engineering capabilities across the organization. If you’re the kind of engineer who thrives at the intersection of architecture, hands-on development, and future-facing analytics—this is a rare opportunity to make a global impact at scale.

Requirements

• Bachelor’s degree in a STEM field or equivalent experience.
• Extensive hands-on experience as a senior IC in data engineering, analytics engineering, or data architecture (typically 8+ years).
• Expert-level SQL and data modeling skills on large-scale platforms (Snowflake preferred).
• Strong experience building production data pipelines and models using Python, cloud services, and modern data stack tools.
• Proficiency with dbt or similar transformation frameworks.
• Demonstrated ability to set technical direction, define architectural patterns, and establish engineering best practices.
• Solid experience with Git/GitHub workflows, including branching strategies and collaborative development.
• Experience building and maintaining CI/CD pipelines in GitHub Actions , including automated testing and secure deployments.
• Ability to operate across both analytics engineering and data engineering responsibilities.

Nice To Haves

• Experience with Dagster , Airflow, or similar orchestration tools.
• Familiarity with streaming or event-based processing (Kafka, Fink, Kinesis).
• Experience supporting ML/AI workflows or integrating ML into data products.
• Master’s degree in a STEM field.
• Prior experience as a Staff or Senior Staff-level engineer.

Responsibilities

• Set architectural strategy for data modeling, transformation, ingestion, and data products, and guide engineering best practices across teams.
• Lead analytics engineering by designing high-quality Snowflake/dbt models, establishing governance and testing standards, and mentoring engineers in scalable modeling and system design.
• Build and evolve data pipelines using Python, Spark, APIs, connector frameworks, and other ingestion technologies, introducing automation, observability, and resilient design patterns.
• Collaborate cross-functionally with product, engineering, and data science to shape impactful, scalable solutions.
• Drive future advanced analytics and ML capabilities by defining feature pipelines, supporting classical ML models, and enabling new AI-driven workloads including LLM-based and hybrid ML/AI architectures.

Benefits

• comprehensive medical, vision, dental, and life, AD&D, short-term and long-term disability insurance, sleep care management, Health Savings Account (HSA), Flexible Spending Account (FSA), commuter benefits, 401(k), Employee Stock Purchase Plan (ESPP), Employee Assistance Program (EAP), and tuition assistance
• Employees have flexible time off (FTO), receive 11 paid holidays plus 3 floating days and are eligible for 14 weeks of primary caregiver or two weeks of secondary caregiver leave when welcoming new family members.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees