• Play a critical role in expanding product offerings across the tech stack • Analyze tough customer problems and design efficient backend solutions • Design, develop, and maintain scalable systems and features • Work with business team to build user stories from requirements

• Build end-to-end GTM workflows across targeting, enrichment, scoring, routing, sequencing, and reporting • Reduce manual work while improving speed, consistency, and data quality • Implement ICP rules, intent signals, and decision logic that hold up at scale • Connect Hubspot, Salesforce, enrichment tools, outbound platforms, and automation into a single operating system • Ensure GTM execution scales without breaking deliverability or data integrity • Build dashboards that surface funnel health, lead quality, and pipeline performance, and identify where leads drop off so you can fix the system, not the symptom • Translate business requirements into technical workflows across Marketing, SDR, Sales, RevOps, and CS • Create scripts or automations when off-the-shelf tools fall short, debug broken workflows and integration issues, and maintain clean documentation so systems scale beyond you

• Design, build, and maintain scalable APIs, services, and data pipelines primarily in Python, leveraging microservices and cloud-native architectures. • Implement secure, high-performance, and maintainable system designs that can evolve with business and healthcare needs. • Develop web applications and dashboards (React/Next.js or similar) that surface backend and AI functionality to internal and external users. • Integrate and refine LLM workflows including prompt engineering, model orchestration, and backend/UX pipelines for intelligent healthcare solutions. • Ensure engineering excellence through code reviews, testing, CI/CD automation, observability, and performance optimization. • Guide technology decisions, frameworks, and best practices for software development. • Lead and mentor junior engineers and offshore development teams. • Stay up to date with industry trends and emerging technologies to drive continuous improvement. • Provide technical documentation and architectural diagrams for system enhancements. • Work closely with Product Management to define technical requirements and roadmap initiatives. • Collaborate with UX/UI teams to ensure seamless and intuitive user experiences. • Integrate backend APIs and microservices for efficient data exchange across platforms. • Partner with data analytics teams to optimize performance and scalability.

• Lead the design, implementation, and expansion of the company's data platform, including ingestion pipelines, data warehouse/lakehouse architecture, transformation layers, and data serving infrastructure. • Define and champion engineering standards, best practices, and architectural patterns for data infrastructure across the organization. • Collaborate cross-functionally to understand data needs and translate them into scalable, reliable platform capabilities. • Drive technical decisions on tooling, frameworks, and vendor selection for the data stack (e.g., orchestration, storage, transformation, observability). • Mentor and level up engineers on the team, providing technical guidance and code review with a focus on quality and long-term maintainability. • Proactively identify scalability, reliability, and performance bottlenecks and lead efforts to address them. • Partner with stakeholders across engineering, data science, and business teams to ensure the platform supports current and future analytical and operational needs. • Contribute to organizational planning and hiring, helping grow the data engineering function.