Data Architect

Role: Data Architect

Location: Irvine CA onsite

Employment type: Contract

Data Architect - Onshore (SoCal)

Data Platform Architecture

End-to-end architecture for a Unified Data Platform spanning manufacturing, enterprise, and analytics domains

Define reference architectures for data ingestion, storage, processing, analytics, and AI enablement

Drive convergence of structured, semi-structured, unstructured, telemetry, and time-series data into a cohesive platform across data technologies

Establish clear platform patterns (lakehouse, streaming-first, event-driven, domain-oriented)

Domain Context

Familiarity with semiconductor manufacturing data landscapes (fab, test, assembly, packaging)

Ability to bridge OT and IT data architectures in regulated manufacturing environments

Data Lakehouse Architecture

Design and governance of lakehouse architectures

Strong experience with:

Data lake zoning (raw, curated, trusted, feature layers)

Warehouse and analytics integration

Semantic and consumption layers

Define standards for data modeling, partitioning, schema evolution, and performance optimization

Architect for multi-consumer access (BI, data science, ML, operations)

Cloud & Infrastructure Architecture

Hands-on architectural experience with cloud-native data platforms, Databricks, Azure, and Google Cloud Platform

Architecture-level knowledge of:

Object storage

Cloud data warehouses

Streaming and messaging platforms

Infrastructure-as-Code design standards (Terraform)

Design for resilience, scalability, and cost optimization (FinOps-aligned)

Streaming, Telemetry & Real-Time Enablement

Architect pipelines for manufacturing telemetry

Experience designing platforms using:

Event-driven ingestion

Streaming analytics

Time-series data management

Enable operational analytics and alerting without compromising analytical workloads

AI / ML Data Enablement

Architect data foundations for AI-driven use cases

Define feature stores, training datasets, and inference data paths

Experience with graph-oriented or knowledge-based architectures for relationship-driven analytics

Ensure data architecture supports model lifecycle management and reusability.

Enterprise & Application Integration

Architect integration patterns across data workloads

Enable correlation of business, manufacturing, and operational data into unified analytical views

Data Governance, Security & Compliance

Define enterprise data governance frameworks aligned to platform architecture

Architect solutions for:

Metadata management

Data lineage and traceability

Master and reference data strategies

Design security-by-default data architectures (RBAC, encryption, segmentation)

Familiarity with compliance considerations relevant to semiconductor manufacturing and IP protection

Observability, Reliability & Platform Operations

Architect data platform observability (pipeline health, data quality, SLAs)

Define operational models for:

Incident response

Root cause analysis

Platform reliability

Enable clear ownership boundaries between platform, domain, and consumption teams

Collaboration, Enablement & Leadership

Serve as a technical bridge between:

Manufacturing engineering

Data engineering

Data science / AI teams

Enterprise IT and security

Create architecture artifacts: reference diagrams, standards, design patterns

Mentor engineers and guide implementation without becoming a delivery bottleneck

Comfortable operating in matrixed, globally distributed organizations with onshore leadership presence.