Design and deploy modern cloud-based data architectures, lead solution design discussions, and enable data solutions at scale for enterprise clients.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
General Info:
Must be a US Citizen or GC Holder
Fully Remote
Contract to Hire
Overview:
Seeking a highly skilled Resident Solutions Architect to support enterprise-level engagements focused on modern data architecture, cloud platforms, and advanced analytics initiatives. The role is both strategic and hands-on- serving as a technical advisor while designing, deploying, and enabling modern data and cloud solutions in customer environments. Candidates should bring a strong consultative approach, technical depth across cloud ecosystems, and experience enabling data solutions at scale.
Key Responsibilities:
- Serve as a trusted technical consultant to enterprise clients, aligning architectural decisions with business objectives.
- Design and deploy modern cloud-based data architectures leveraging distributed systems, containerization, and automation.
- Lead solution design discussions, architecture diagrams, data modeling efforts, and implementation roadmaps.
- Develop and optimize scalable pipelines, workflows, and data governance strategies supporting analytics and AI workloads.
- Partner with engineering teams to implement CI/CD, infrastructure-as-code, observability, and platform standards.
- Deliver best-practice enablement through workshops, documentation, and knowledge transfer.
Required Qualifications:
- 5+ years designing and implementing large-scale cloud or data architecture solutions.
- Expert-level experience with at least one major cloud platform (AWS, Azure, GCP).
- Hands-on experience with containerization (e.g., Docker, Kubernetes) and modern DevOps tooling.
- Strong communication skills and ability to present architectural decisions to technical and business stakeholders.
- Proven history supporting enterprise clients or consulting engagements.
Preferred Qualifications:
- Experience with distributed data systems (e.g., Spark, Databricks, Snowflake).
- Familiarity with data governance, metadata management, and security frameworks.
- Background working on ML/AI-enabling platforms or production pipelines.
- Prior experience in customer-facing architecture or solutions engineering roles.