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.

Job Details

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 companys 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:

• 25 years of professional software engineering experience

• Bachelors or Masters 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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