Data Platform Architect (Contract / Staff Augmentation)
Mandatory –
Job Summary
The Data Platform Architect is responsible for defining and governing the enterprise data platform architecture that supports analytics, reporting, and AI/ML initiatives. The role ensures data platforms are scalable, secure, reliable, and cost-efficient while aligning with business and technology strategies. Working closely with Product Management, Data Engineering, Cloud, Security, and Analytics teams, the architect provides technical leadership, establishes standards and reference architectures, and drives the evolution of enterprise data capabilities.
Key Responsibilities
- Define and maintain enterprise data platform strategy, architecture standards, and design patterns.
- Develop target-state architectures, technical documentation, and architectural roadmaps.
- Evaluate and govern data platform, integration, and ETL/ELT technology selections.
- Provide architectural guidance for data pipelines, analytics platforms, and integration solutions.
- Establish standards for scalability, reliability, observability, security, and disaster recovery.
- Ensure compliance with data privacy, governance, and regulatory requirements.
- Standardize data integration approaches, including batch, streaming, and event-driven architectures.
- Partner with engineering teams to translate architectural standards into implementable solutions.
- Drive cost-efficient platform design and support FinOps initiatives.
- Assess emerging technologies and recommend architectural improvements, including AI-enabled data engineering capabilities.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Data Science, or related field.
- 7+ years of database engineering experience, including 3+ years in architecture design.
- Master's degree and healthcare domain experience preferred.
- Experience with enterprise integrations, APIs, and modern cloud-based data ecosystems.
Required Skills
Data Platforms & Databases
Data Engineering
- ETL/ELT architecture and orchestration (Matillion)
- Data modeling and governance
- Batch, streaming, and event-driven integrations
- Data lineage, observability, and reliability engineering
Cloud & Automation
- Infrastructure as Code (IaC)
- Platform automation and operational readiness
Programming & Analytics
- Analytics-ready dataset design
- AI/ML data platform enablement
Integration & Enterprise Systems
- API integrations (Apigee)
Soft Skills
- Stakeholder communication and presentation
- Problem-solving and strategic planning
- Agile and Waterfall delivery methodologies
