Software Engineer II - Data & Applications (Hybrid, Clinton PA)

We are constantly looking to add to our core talent. If you are seeking a career that is challenging and rewarding, a work environment that is diverse and dynamic, look no further — Haemonetics is your employer of choice.

We are seeking a Software Engineer II – Data & Applications to design, develop, and support full-stack data-driven applications across edge and cloud environments. This role blends software engineering and data engineering disciplines, focusing on front-end interfaces, backend APIs, data pipelines, and real-time streaming systems.

You will play a key role in developing production-quality systems, supporting edge-to-cloud data integration, and collaborating with cross-functional teams spanning manufacturing, data science, and operations. The ideal candidate is self-motivated, comfortable working across multiple layers of the technology stack, and ready to help shape the company’s data architecture.  This role may require up to 50% travel and is Hybrid (3 days per week) in our Clinton, PA Manufacturing Facility.

Key Responsibilities:

• Design, implement, and maintain full-stack applications with a focus on performance, scalability, and reliability

• Develop and manage APIs (REST, gRPC, GraphQL) for internal and external system communication

• Architect, build, and optimize data pipelines and ETL processes (batch and streaming)

• Work with message buses and data streaming frameworks (Kafka, MQTT, etc.)

• Design and evolve database schemas (SQL and NoSQL) to support application and analytics needs

• Deploy and support applications across Linux-based edge and cloud environments

• Integrate data from edge computing platforms (Litmus Edge preferred) with central systems

• Collaborate with data scientists and analytics engineers to support model deployment and data services

• Implement observability (logging, metrics, monitoring) for data and application reliability

• Participate in code reviews, architecture reviews, and cross-team technical discussions

• Mentor junior engineers and support their technical development

• Travel (up to 50%) to support integration and deployment at North American sites

Required Qualifications:

• 2–5 years of professional software engineering experience

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or related field (or equivalent experience)

• Proficiency in backend programming languages such as Python, Java, C#, or Go

• Working experience with front-end frameworks (e.g., React, Angular, or Vue)

• Solid understanding of RESTful API design, versioning, and authentication methods

• Experience designing and maintaining relational and non-relational databases

• Familiarity with streaming technologies (Kafka, MQTT, or similar) and data pipeline design

• Experience developing on Linux systems, including scripting and performance debugging

• Strong understanding of software architecture, data modeling, and integration concepts

• Excellent problem-solving, analytical, and debugging skills

• Ability to balance multiple projects and collaborate effectively across teams

Preferred Qualifications:

• Hands-on experience with Litmus Edge or other edge computing frameworks

• Tulip Interfaces implementation and app development experience

• Experience with containerization and orchestration (Docker, Kubernetes)

• Familiarity with cloud platforms (AWS, Azure, GCP) and cloud-native data tools

• Experience with monitoring and observability tools (Prometheus, Grafana, ELK)

• Exposure to CI/CD pipelines, GitOps, and automated testing frameworks

• Experience integrating or deploying machine learning models in production environments

• Understanding of industrial IoT (IIoT) data protocols and edge-to-cloud architectures

Career Growth Opportunities

• Lead design of subsystems and large-scale integration projects

• Serve as a technical mentor and subject matter expert for edge and data systems

• Progress into Senior Software Engineer or Data Engineering Specialist roles

• Collaborate with cross-functional teams driving analytics, automation, and manufacturing innovation

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