- Define current-state and future-state data architecture across enterprise platforms and applications.
- Design scalable data foundations across cloud and hybrid environments.
- Establish standards across data ingestion, storage, transformation, modeling, metadata, lineage, quality, and governance.
- Create architecture patterns for batch, streaming, event-driven, and API-based data integration.
- Develop conceptual, logical, and physical data models aligned with business and technical requirements.
- Assess existing data platforms and identify gaps across scalability, quality, governance, integration, security, and accessibility.
- Partner with engineering, product, analytics, security, and business teams to ensure enterprise data is trusted, usable, and properly governed.
- Support data architectures that enable analytics, generative AI, retrieval-augmented generation, and other emerging technology use cases.
- Evaluate data platforms, tools, and technologies based on scalability, security, maintainability, and business needs.
- Translate complex technical concepts into clear recommendations, roadmaps, and architecture documentation for technical and executive stakeholders.
Requirements
- 8+ years of experience in data architecture, enterprise data platforms, data engineering, or a related field.
- Demonstrated experience designing or building scalable enterprise data foundations.
- Strong knowledge of data modeling, integration architecture, metadata, lineage, governance, data quality, and master data management.
- Experience with modern data platforms such as Snowflake, Databricks, BigQuery, Redshift, Synapse, or comparable technologies.
- Experience architecting data solutions in AWS, Azure, GCP, or hybrid cloud environments.
- Strong understanding of data lakes, lakehouses, data warehouses, and modern data platform architecture.
- Experience designing batch, streaming, event-driven, and API-based data architectures.
- Strong understanding of data security, privacy, access control, and responsible data usage.
- Ability to assess complex environments and translate findings into practical architecture and implementation roadmaps.
- Strong communication and stakeholder management skills.
- Must be based in the Los Angeles area and able to work onsite three days per week.
Core Competencies
Expertise in designing scalable data architectures across cloud and hybrid environments, with a strong focus on data modeling, integration, governance, and security. Proven ability to collaborate with cross-functional teams to ensure data quality and usability while translating complex technical concepts into actionable strategies.
Highest-signal resume keywords
- Data Architecture
- Data Modeling
- Cloud Environments (AWS, Azure, GCP)
- Data Governance
- Data Integration
ATS Optimization Keywords
Hard Skills
- Data Architecture
- Data Modeling
- Data Integration
- Data Governance
- Data Quality
- Master Data Management
- Batch Architecture
- Streaming Architecture
- API-Based Architecture
- Data Security
Soft Skills
- Strong Communication
- Stakeholder Management
Industry Keywords
- Enterprise Data Platforms
- Data Lakes
- Lakehouses
- Data Warehouses
- Data Lineage
Tools & Technologies
- Snowflake
- Databricks
- BigQuery
- Redshift
- Synapse