Data Solutions Architect - Data Platform, Data Products & AI-Ready Data
Applied Materials3 days ago
Base Salary
$180k - $247k/yr
Responsibilities
- Architect enterprise-scale data platforms, data lakes, lakehouses, integrations, batch and streaming systems, storage, transformation, serving, analytics, and downstream consumption.
- Provide technical leadership for platform production support, availability, reliability, scalability, performance, security, service levels, data freshness, and operational sustainability.
- Lead resolution of complex production issues, root-cause analyses, corrective actions, architecture improvements, automation, and platform standards.
- Establish standards for monitoring, observability, alerting, data quality, disaster recovery, backup and recovery, capacity planning, and production readiness.
- Architect multi-tenant data environments and security and governance patterns covering identity, access, metadata, lineage, auditability, encryption, retention, and secure data sharing.
- Define enterprise standards for data products, data contracts, semantic layers, business glossaries, ontologies, knowledge graphs, and AI-ready data foundations.
- Drive architecture modernization, DataOps, DevSecOps, FinOps, infrastructure automation, testing automation, deployment automation, and cloud cost optimization.
- Lead complex data-platform initiatives within scope, timeline, budget, architecture, security, and quality guardrails.
- Collaborate across engineering, infrastructure, cybersecurity, governance, architecture, AI/ML, application, and business teams.
- Mentor architects, technical leads, and engineers and promote reusable architecture patterns and engineering best practices.
Requirements
- Significant depth and breadth in enterprise data architecture, cloud data platforms, data lakes, lakehouse architecture, distributed data processing, and modern data engineering.
- Advanced knowledge of Databricks, Apache Spark, Delta Lake, Apache Iceberg, SQL, Python, cloud object storage, and distributed computing architectures.
- Strong understanding of batch, streaming, event-driven, and near-real-time architectures, including Kafka, Spark Structured Streaming, and Change Data Capture.
- Expertise in data products, Data Mesh concepts, metadata management, data contracts, semantic models, business glossaries, ontologies, and knowledge graph architectures.
- Knowledge of AI/ML and GenAI data architecture, including Retrieval-Augmented Generation, vector search, semantic retrieval, Text-to-SQL, AI-ready datasets, and agentic AI consumption.
- Strong knowledge of data governance, security, privacy, lineage, data quality, observability, RBAC, policy-based access, encryption, and multi-tenant isolation.
- Knowledge of DataOps, DevSecOps, Infrastructure as Code, CI/CD, production operations, Site Reliability Engineering, disaster recovery, and FinOps.
- Experience providing senior technical leadership across enterprise data platform initiatives and influencing multiple teams without direct organizational authority.
- Ability to lead architecture reviews, critical production incidents, complex technical initiatives, stakeholder alignment, and architecture governance.
- Ability to evaluate architecture tradeoffs involving business value, security, scalability, reliability, interoperability, maintainability, operational complexity, and cost.
Benefits
- Full-time regular employee position in Santa Clara, California.
- No travel required.
- Relocation eligible.
- Comprehensive benefits package, with potential bonus and stock award program eligibility.
- Supportive work culture focused on learning, development, health, and wellbeing.
Tech Stack
Categories
Data Engineering
About Applied Materials
Applied Materials builds semiconductor and display manufacturing equipment and related materials engineering technologies used by chip and flat-panel makers. It sells capital tools, process technology, and lifecycle services and software to support high-volume wafer fabrication and display production worldwide. Founded in 1967 and headquartered in Santa Clara, California, the company is publicly traded on NASDAQ under the ticker AMAT.