Technical Business Analyst/Requirement Manager IRC302362

Description
The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.
The project is a cloud-based PaaS Ecosystem built with a privacy by design centric approach to provide a centralized cloud-based platform to store, classify, and control access to federated datasets in a scalable, secure, and efficient manner.
The ecosystem will allow Customer Operating Units (medical device departments) to store federated data sets of varying sizes and formats and control access to those data sets through Data steward(s). Source data sets can be exposed to qualified use cases and workflows through different project types.
The Healthcare Data Platform ecosystem will provide ML/AI project capabilities for streamlined development processes and a ML/AI workbench to enhance data exploration, wrangling, and model training.
OU’s: Currently, Nuero, Cardio, Diabetes is the OU that HDP data platform is working with, but there could be more OU’s coming up with requirements in future.
GL Role: is to work on the enhancement of current capabilities, including taking over the work that AWS proserve team is doing, and develop new requirements that will keep coming from different OU’s in the future.

Requirements
As a System Engineer within the Company Research & Systems Engineering team, you will have the opportunity to work on cloud-based solutions with a strong focus on AWS, Data Engineering, and scalable data platforms. You will collaborate with cross-functional engineering teams to design, develop, integrate, and maintain reliable cloud-native systems and data workflows.
In this role, you will contribute to building and evolving AWS-based architectures, data processing pipelines, and integrations across distributed systems. You will develop a strong understanding of end-to-end system architecture, data flows, infrastructure, and operational requirements, helping to drive technical implementation and delivery throughout the software development lifecycle.
You will work closely with software engineers, data engineers, architects, and other stakeholders to ensure that solutions are scalable, secure, maintainable, and aligned with both technical and business requirements.

• 3+ years of experience in System Engineering, Software Engineering, Cloud Engineering, Data Engineering, or a related technical role.
• Strong software development experience with Python.
• Hands-on experience designing, developing, or supporting solutions on AWS.
• Experience with data engineering concepts and technologies, including data ingestion, ETL/ELT, transformation, validation, and data processing pipelines.
• Strong SQL skills and experience working with relational and/or NoSQL databases.
• Experience with REST APIs, service integrations, and distributed application architectures.
• Understanding of cloud-native architecture principles and modern software development practices.
• Experience troubleshooting applications and distributed cloud systems and performing root cause analysis.
• Experience with Git and modern CI/CD development workflows.
• Strong analytical and problem-solving skills with the ability to understand complex systems and data flows.
• Ability to work effectively with software, data, cloud, and machine learning engineering teams.
• BA/BS in Computer Science, Software Engineering, Information Technology, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience with AWS data services such as S3, Glue, Athena, EMR, or similar technologies.
• Experience with Amazon SageMaker and machine learning development or deployment workflows.
• Experience with Infrastructure as Code using AWS CloudFormation, Terraform, or AWS CDK.
• Experience with AWS monitoring and observability services such as CloudWatch and CloudTrail.
• Experience working in Agile/Scrum development environments.

Job responsibilities

• Work with engineering and cross-functional stakeholders to gather, analyze, clarify, and document business, functional, and non-functional requirements, translating them into clear system and technical requirements.
• Define system requirements, interfaces, data flows, integration requirements, acceptance criteria, and technical constraints for cloud-based software components, data platforms, and integrations.
• Maintain requirements throughout the development lifecycle, ensuring traceability between business needs, system requirements, technical design, implementation, and validation.
• Identify gaps, dependencies, assumptions, and potential technical risks in requirements and work with stakeholders to resolve them before and during implementation.
• Design and contribute to scalable AWS-based architectures supporting data ingestion, processing, transformation, storage, and distribution.
• Analyze data and system behavior to support architecture, implementation, performance, and product decisions.
• Collaborate with Data Engineering, Software Engineering, Cloud Engineering, DevOps, and Architecture teams to design and integrate end-to-end cloud solutions.
• Support operational monitoring, logging, alerting, and troubleshooting of cloud applications and data processing workflows.
• Contribute to system architecture and technical design discussions, including scalability, reliability, security, performance, and cost considerations.
• Participate in technical and requirements reviews to ensure solutions meet defined requirements, engineering standards, cloud best practices, and established software development processes.
• Support continuous improvement of cloud infrastructure, data pipelines, deployment processes, requirements management, and engineering practices throughout the software development lifecycle.