Data Platform Architect

**Company Description**
Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape.

Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality.

Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward.

We are seeking a **hands-on Data Platform Architect** to lead the design, implementation, and modernization of our enterprise-wide data platform—including data governance, lakehouse architecture, engineering pipelines, analytics, and AI-driven solutions. This role requires deep technical expertise, strategic vision, and executional leadership to build a scalable, governed, and intelligent data ecosystem across cloud and on-prem environments.

**ESSENTIAL DUTIES AND RESPONSIBILITIES**:
**Architecture & Strategy**
- Define and continuously evolve the target data architecture across the stack—governance, engineering, modeling, lakehouse, AI/ML.
- Translate business and technical goals into scalable and resilient platform designs.
- Own and maintain architectural roadmaps, standards, and decision frameworks.
- Act as the bridge between architects, Business SME/Analysts, data engineers, and analytics teams to ensure alignment and compliance with platform standards.

**Data Engineering & Platform Delivery**
- Design and implement modern ELT/ETL pipelines using tools like Spark, Python, SQL, Scala, and cloud-native components (e.g., Fivetran, **Databricks**, Snowflake, BigQuery).
- Build and maintain Lakehouse platforms using Delta Lake, Iceberg, or equivalent technologies.
- Manage data ingestion from heterogeneous sources including ERP, CRM, IoT, and third-party APIs.
- Guide hands-on development of robust, reusable, and automated data flows.

**Governance, Metadata, and Quality**
- Implement and enforce data governance frameworks including data lineage, metadata management, and access controls.
- Partner with Data Stewards and Governance Analysts to catalog data domains, define entities, and ensure SOX compliance.
- Drive adoption of tools like and Atlan/Unity Catalog for metadata, quality, and stewardship.
- Develop data models (ERDs, dimensional and 3NF) and define canonical data representations.

**AI & Agentic Enablement**
- Lead the integration of AI/ML solutions and agentic architectures into the data platform to automate insights, recommendations, and decision flows.
- Collaborate with AI/ML teams to embed vectorization, tokenization, and semantic enrichment into the data stack.

**Collaboration & Leadership**
- Review solution designs and provide architectural guidance to engineering teams.
- Mentor technical staff while fostering best practices and continuous improvement.
- Collaborate with DevOps to embed CI/CD, version control, and environment automation across the data lifecycle.
- Continuously assess and improve platform reliability, scalability, performance, and cost-efficiency.

**Qualifications** REQUIRED**:

- 12+ years of hands-on experience in data architecture, engineering, and analytics delivery.
- Proven success in building modern data platforms on cloud (AWS, **Azure**, GCP).
- Deep knowledge of data lakehouse architectures (e.g., Databricks, Fabric).
- Proficiency with Python, SQL, Spark, and orchestration frameworks.
- Experience with ETL/ELT tools (e.g., Informatica, Talend, Fivetran) and containerization (Docker, Kubernetes).
- Strong background in Data Modeling (ERD, star/snowflake, canonical models).
- Familiarity with REST APIs, GraphQL, and event-driven design.
- Demonstrated experience integrating AI/ML and GenAI components into data platforms.

**PREFERRED**:

- 15+ years of experience including solution architecture roles for large-scale data initiatives.
- ** Deep expertise in Databricks, Delta Lake, Unity Catalog and Azure Data Services**:

- Experience with BI/visualization tools like Power BI, Tableau, and Looker.
- Understanding of Master Data Management, data profiling, cleansing, and enrichment techniques.
- Exposure to DataOps and DevOps practices for CI/CD and platform automation.
- Strong analytical and problem-solving skills with the ability to communicate c