Job Description: Technical Architect - Senior Data Solutions Engineering (AWS-Python-FastAPI-React-DevOps)

We are seeking an experienced senior-level engineer (10+ years) to design and deliver cloud-native data solutions and customer-facing data solutions on AWS as a Technical Architect. This role blends data engineering/analytics, backend API development (Python/FastAPI), and frontend development (React). The candidate will own solution design, build and maintain reliable data pipelines and analytical outputs, perform data exploration and analysis to translate ambiguous questions into measurable insights, and identify opportunities to integrate AI capabilities into data products and workflows. The role requires working independently, owning end-to-end delivery, and driving technical conversations with strong communication and stakeholder management, while supporting team delivery through peer reviews and occasional mentoring.

10+ years of professional software engineering experience, with significant time delivering production systems.
Strong hands-on experience with AWS and designing scalable, secure, and cost-effective cloud-native data and application architectures.
Proficiency in Python and building APIs/services using FastAPI (or similar Python frameworks); strong React experience building modern, responsive web applications.
Demonstrated experience delivering data solutions - pipelines, data modeling, analytics enablement, or BI support - that support business decision-making.
Solid understanding of software architecture, design patterns, and tradeoffs (performance, scalability, cost, security).
Strong communication skills: able to lead conversations with technical and non-technical stakeholders, clarify requirements, and present technical decisions and recommendations.
Experience working independently in ambiguous environments, owning workstreams end-to-end (requirements, design, build, test, deploy, documentation) and driving work to closure.
Implements CI/CD, monitoring/alerting, logging, and secure-by-design practices; participates in code reviews and helps establish engineering standards.
Experience with AWS data services.
Experience with containers and orchestration (e.g., Docker, ECS/EKS) and infrastructure-as-code (e.g., Terraform, CloudFormation).
Strong SQL skills and familiarity with data modeling approaches (dimensional, normalized, lakehouse patterns).
Experience implementing MLOps practices and/or integrating LLM-based capabilities into applications.
Familiarity with data observability tooling (metrics, tracing, dashboards) and production support practices.
Strong communication skills - able to lead conversations with technical and non-technical stakeholders, clarify requirements, and present technical decisions and recommendations.
Comfortable working independently in ambiguous environments, proactively managing risks and dependencies to closure.
Collaborative team player who supports peer reviews and occasional mentoring of other engineers.
Enthusiastic and practical about applying AI/ML-enabled solutions to business problems.