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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Engineer, Enterprise Data Platform - **Company:** SanDisk - **Location:** Milpitas, CA, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, BigQuery, Cloud Engineering, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Profiling, Data Security, Data Visualization, DevOps, Python (Programming Language), Metadata, Meta-Data Management, Metadata Repositories, SAP ERP, Power BI, DataOps, SAP (Applications), Scala (Programming Language), SQL Databases, Data Streaming, Systems Integration, Tableau (Software), Talend, Enterprise Data Management, Google Cloud, Data Ingestion, System Availability, Snowflake, Apache Spark, Event Driven Architecture, Containerization, Data Lakes, Kubernetes, Infrastructure Automation Frameworks, Data Lineage, Graphql, Data Management, Data Lakehouse, Restful APIs, Looker Analytics, Software Version Control, Docker, Databricks, Web Api - **Published:** September 24, 2026 - **Apply:** https://www.thejobnetwork.com/job/60facce5-4271-4186-8767-bfbf55bbd8d8/senior-staff-engineer-enterprise-data-platform ## About the Role * 9+ 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. * 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 clearly to both technical and business audiences. * Knowledge of high-tech business domains such as engineering, sales, finance, supply chain, or semiconductor operations is a strong plus. * Knowledge of SAP and SAP-BDC a plus ## Description We are seeking a hands-on Senior Staff Engineer, Enterprise Data Platform 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., Architecture & Strategy * Define and continuously evolve the target data architecture across the stack-Data Governance, data engineering, data modeling and Databricks lakehouse in Azure and GCP * 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 * Build and maintain Databricks Lakehouse platforms using Delta Lake, Iceberg, or equivalent technologies. * Design and implement modern ELT/ETL pipelines using tools like Spark, Python, SQL, Scala, and cloud-native components (e.g., Fivetran, Databricks, Snowflake, BigQuery). * 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 in Azure and GCP 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 Atlan and Unity Catalog for metadata, quality, and stewardship. * Develop data models (ERDs, dimensional and 3NF) and define canonical data representations. * Define and maintain Data Products including end to end data flows, Data Lineage, Data Access and Data Catalog 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)