Role: Databricks Architect with AWS
Location: 100% Remote
Experience: 12+ Years
Employment Type: Contract
H1B Accepted on C2C
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Job Overview
We are seeking an experienced Databricks Architect with strong AWS expertise to design and govern enterprise-scale data platforms using Databricks and modern cloud data architecture principles.
The ideal candidate will have deep expertise in Databricks Lakehouse, Delta Lake, Unity Catalog, data modeling, security, orchestration, and MLOps/feature store architecture, along with the ability to translate architecture into scalable, production-ready implementations.
This role goes beyond solution design you will be responsible for architecture governance, design-to-build execution, cross-domain decision-making, standards enforcement, scalability, and technical debt management.
Required Technology & Platform Knowledge
- Databricks: Lakehouse, Delta Lake, Unity Catalogue
- AWS Cloud: Strong hands-on architecture experience
- Medallion Architecture: Bronze, Silver, Gold
- Enterprise Data Modeling Standards
- Data Security & Access Architecture
- Data Governance & Architecture Standards
- Orchestration & Pipeline Tooling
- MLOps & Feature Store Architecture
- Data integration and enterprise data platform architecture
- Performance, scalability, reliability, and cost optimization
Preferred Qualifications
- 12+ years of experience in Data Architecture / Cloud Data Architecture
- Strong hands-on experience with Databricks and AWS
- Experience designing enterprise Lakehouse architectures.
- Strong understanding of Delta Lake and Unity Catalog
- Experience implementing Medallion Architecture
- Strong data modeling and data governance background
- Experience with enterprise security, IAM, RBAC, and access-control architecture.
- Experience with data orchestration and modern data pipelines.
- Knowledge of MLOps, ML platforms, and Feature Stores
- Strong understanding of cloud cost optimization and performance tuning
- Excellent communication, stakeholder management, and technical leadership skills
- Ability to work independently in a 100% remote environment.
Key Responsibilities
Design-to-Build Handoff
- Translate high-level architecture and design specifications into clear, buildable technical specifications for Data Engineering and STS teams.
- Ensure implementation teams understand architectural decisions, dependencies, standards, and non-functional requirements.
- Provide technical guidance throughout the development lifecycle.
Cross-Domain Architecture & Data Model Arbitration
- Resolve conflicting data models and architectural approaches across business and technology domains.
- Establish enterprise-wide modeling standards and prevent domain-specific solutions from creating downstream integration issues.
- Drive alignment and make architecture decisions where multiple teams or domains are impacted.
Technical Debt Governance
- Monitor and track deviations between approved architecture and actual implementation.
- Identify architectural drift, technical debt, scalability concerns, and potential downstream risks.
- Establish remediation strategies and prioritize architectural improvements.
Standards Enforcement
- Review active/live implementations against established architecture, engineering, security, and data modeling standards.
- Ensure architecture governance continues throughout implementation rather than being limited to the initial design phase.
- Conduct architecture and technical design reviews as required.
Scalability & Reusability
- Design data models, frameworks, and platform capabilities as reusable enterprise assets rather than isolated domain-specific solutions.
- Establish common patterns and reusable architecture components across data domains.
- Ensure solutions can scale with increasing data volumes, users, workloads, and business requirements.
Architecture Risk & Decision Ownership
- Own the technical implications and downstream impact of major architecture decisions.
- Evaluate trade-offs involving performance, scalability, security, maintainability, and AWS/Databricks costs.
- Proactively identify risks across dependent domains and recommend appropriate architectural solutions.
