Job Description Summary

We are looking for an experienced Staff Software Engineer to lead the design and delivery of large-scale, cloud-native and data-intensive systems on AWS. This role demands deep hands-on expertise in application development, data engineering, and system architecture, with a strong emphasis on building complex, secure, and highly reliable data pipelines and large-scale data solutions using Databricks and modern analytics platforms.

As a Staff Engineer, you will operate at a strategic and highly technical level—owning end-to-end solution design, defining architectural standards, and driving engineering direction. You will tackle complex data and platform challenges, mentor and elevate engineering team members, and deliver business-critical outcomes through scalable, secure, and high-impact solutions. The role also requires a strong learning mindset, a willingness to adapt to evolving technologies, and the ability to balance deep technical execution with broader organizational influence.

GE Healthcare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world.

Job Description

Architecture & System Design

• Design and lead the development of highly scalable, low-latency systems.
• Architect event-driven and microservices-based systems on AWS.
• Define best practices for:
•  Fault tolerance and resilience
•  Data-intensive applications and pipelines
• Drive decisions on partitioning, caching, and load balancing.

Cloud-Native Application Development

• Build and maintain production-grade backend systems using Python.

• Develop APIs using REST with strong versioning and backward compatibility practices.

• Ensure high-quality code through rigorous code reviews, refactoring, and performance tuning.

Data Engineering using Databricks

• Design and implement end-to-end data pipelines using Databricks (Apache Spark, Delta Lake) across ingestion, transformation, and consumption layers.

• Build scalable, resilient ETL workflows for both structured and unstructured data, supporting batch use cases.

• Implement Delta Lake best practices, including schema enforcement, time travel, CDC handling, and ACID-compliant data operations.

• Optimize data processing for performance and cost using Spark tuning, partitioning strategies, caching.

• Work with large-scale data storage systems such as Amazon S3 and data lakes, enabling efficient lakehouse architectures.

• Apply governance, security, and compliance controls using Unity Catalog for fine-grained access control, lineage, and auditability.

• Orchestrate and monitor pipelines using Databricks Jobs and Workflows, ensuring operational reliability and SLAs.

• Enable analytics and downstream consumption using Databricks SQL Warehouses, notebooks, and integrations with BI and ML platforms.

Machine Learning Engineering

• Collaborate with data scientists to productionize ML models.

• Build scalable ML pipelines on AWS + Databricks.

• Implement model deployment, monitoring, and lifecycle management.

• Ensure reproducibility, scalability, and performance of ML systems.

Containers & CI/CD

• Build and manage containerized applications using Docker.

• Design CI/CD pipelines and deployment strategies.

Security & Compliance

• Apply secure coding practices and conduct threat modelling.

• Design robust authentication and authorization mechanisms.

• Ensure data protection and compliance standards are met.

Technical Leadership

• Lead design and architecture discussions.

• Write high-quality design documents (RFCs, architecture specs).

• Mentor senior engineers and raise engineering standards.

• Drive alignment across stakeholders in ambiguous environments.

Educational Qualification:

• Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math).

Required Qualifications:

• 8+ years of experience in software engineering.

• Strong proficiency in Python.

• Deep experience with AWS cloud architecture.

• Hands-on expertise in:

  • Databricks, Apache Spark, Delta Lake

  • Data engineering pipelines

• Experience with Docker, microservices architecture.

• Solid understanding of:

  • Concurrency, multithreading, async systems

  • Memory management and performance optimization

• Proven ability to debug complex production systems.

Preferred Qualifications

• Experience building ML platforms or MLOps systems.

• Familiarity with real-time streaming systems (Kafka, Kinesis).

• Experience with large-scale multi-tenant systems.

Inclusion and Diversity

GE Healthcare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership – always with unyielding integrity.

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities.

Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support.

#Everyroleisvital

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Additional Information