Job Description Solution Architect - Data Engineering (Azure Databricks) Location: Remote Rate: $75/hr on C2C Indent: PSL303558-141-5 Role Summary We are seeking a
Solution Architect (Contractor) to design and drive enterprise-scale
data engineering architectures on
Azure Databricks and cloud platforms . This role will define
end-to-end data solutions, architecture patterns, and engineering standards to support analytics, AI/ML, and operational use cases.
The ideal candidate will combine
deep technical expertise with strong business alignment , enabling scalable, secure, and high-performing data platforms.
Solution architecture is critical to ensuring
standardized, scalable, and governed data ecosystems across domains and use cases [NextGen Da...quirements | Meeting] Key Responsibilities 1. Architecture & Solution Design Define and implement end-to-end data architecture (ingestion → transformation → consumption) Design scalable Lakehouse architectures (Databricks, Delta Lake) Develop reference architectures, reusable frameworks, and design patterns Align architecture with performance, scalability, security, and cost optimization goals 2. Data Modeling & Domain Architecture Define canonical data models, dimensional schemas, and semantic layers Architect enterprise data across domains: Claims, Member, Provider, Eligibility Ensure data consistency, interoperability, and reuse across teams 3. Azure Databricks & Cloud Enablement Architect solutions using: Azure Databricks (Mandatory) Azure Data Services (ADF, ADLS, Synapse) Guide engineering teams on: Spark optimization, Delta Lake design, and data pipeline best practices Enable multi-cloud integrations when required 4. Governance, Security & Compliance Define and enforce: Data governance frameworks (lineage, quality, metadata) Access control, RBAC, and data security policies Ensure compliance with: HIPAA, HITRUST, and enterprise regulatory standards Establish data quality SLAs and auditability mechanisms 5. Engineering & Platform Alignment Work closely with: Data Engineering teams Platform Engineering teams AI/ML Engineering teams Provide architectural oversight for pipelines, workflows, and platform capabilities Drive standardization across CI/CD, DataOps, and MLOps practices 6. Stakeholder & Business Engagement Collaborate with business, product, and analytics teams to: Translate requirements into scalable technical solutions Lead architecture reviews, design approvals, and governance forums (ARB) Communicate architecture decisions and trade-offs to leadership Required Skills Strong experience in: Azure Databricks (Mandatory) – PySpark, Delta LakeCloud Architecture (Azure preferred) Deep expertise in: Data Architecture & Data Modeling (OLTP, OLAP, Dimensional) Lakehouse / Data Warehouse design patterns Hands-on experience with: ETL/ELT pipelines and orchestration frameworks CI/CD and DevOps practices (Azure DevOps, Git) Show more Numbers & Facts Location Santa Clara, CA (Remote
Skills
Access Controlunmatched
Architectural Servicesunmatched
Artificial Intelligence (AI)unmatched
Best Practicesunmatched
Cloud Architectureunmatched
Cloud Computingunmatched
Continuous Deployment/Deliveryunmatched
Continuous Integrationunmatched
Cost Controlunmatched
Data Managementunmatched
Data Modelingunmatched
Data Qualityunmatched
Data Warehousingunmatched
Database Extract Transform and Load (ETL)unmatched
Design Patterns Programming Methodologiesunmatched
DevOpsunmatched
Ecosystemsunmatched
Gitunmatched
HIPAA (Health Insurance Portability and Accountability Act)unmatched
Information/Data Security (InfoSec)unmatched
Interoperabilityunmatched
Leadershipunmatched
Maintain Complianceunmatched
Metadataunmatched
Microsoft Windows Azureunmatched
OLAP (OnLine Analytical Processing)unmatched
Regulationsunmatched
Requirements Managementunmatched
Service Level Agreement (SLA)unmatched
Software Engineeringunmatched
Transaction Processing/Managementunmatched
Use Casesunmatched
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