Clinician Nexus

• Collaborate with data platform architects to design and specify platform tooling, services, and integrations • Build data lake and lake house architectures • Build streaming data architectures to support data platform tooling and services • Collaborate with software teams to integrate streaming and batch architectures with software products • Collaborate with data scientists, analysts, and business stakeholders to MVP optimal solutions • Collaborate with data governance teams and data platform architects to build governance into technical solutions • Maintain systems and services that provide transparency and observability into our critical systems • Implement and promote engineering and architectural patterns, perform code reviews, and collaborate in architectural reviews • Collaborate with product team data engineers and architects to MVP data products, maintain data models, and promote data modeling best practice • Provide technical leadership and mentorship to product and data engineers, guiding their growth and professional development and enabling their ability to use platform tooling and services • Lead by example through hands-on contributions to designing, coding, and troubleshooting complex data systems • Identify and address performance bottlenecks and optimization opportunities within data pipelines, databases, and processing frameworks • Optimize data processing workflows to improve efficiency and reduce latency • Lead efforts to diagnose and resolve data-related incidents in a timely manner • Will participate in the grooming of stories • Will be responsible for their own tasking towards the completion of stories • Will mentor junior members of the team and guide junior members on best practice • Will participate in design • Will be responsible for the quality of their own code and will participate in code review of others product • Will be responsible for integrating their own code with the team's DevOps plan and implementation

• Assist in developing and maintaining data pipelines using Python, Databricks, and Delta Lake. • Support infrastructure provisioning and automation using Terraform, Git, and other IaC tools. • Contribute to the design and optimization of data ingestion, enrichment, and streaming processes on AWS and Kafka. • Learn and apply data modeling techniques in platforms such as Reltio (Master Data Management). • Leverage AI-assisted tools to accelerate development, improve code quality, and support documentation and troubleshooting workflows. • Collaborate with engineers across platform, governance, and analytics teams to deliver reliable, high-quality data assets. • Write clean, maintainable code and participate in code reviews and agile ceremonies. • Document processes, tooling, and learnings to support internal knowledge sharing.