Staff Data Platform Engineer (Cloud-Native)

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 building a next-generation cloud-native data platform to support advanced analytics, automation, and data-driven decision-making across manufacturing operations.

We are seeking an experienced Data Platform Engineer with strong backend engineering expertise and exposure to large-scale data systems. In this role, you will design and build scalable, reusable platform services in cloud-native environments that support multiple teams across the organization.

You will play a key role in evolving our organization from delivering isolated data solutions to building a true data platform engineering capability , enabling operational intelligence and analytics at scale.

Why This Role Matters

This role is central to our data platform transformation, moving from delivering individual data solutions to a scalable, cloud-native platform that powers analytics, automation, and operational intelligence.

Engineers in this role will work on modern distributed systems, cloud-native architectures, and large-scale data challenges, while influencing the long-term evolution of our platform and enabling multiple teams to leverage data more effectively.

The role also offers opportunities to take ownership of platform architecture, mentor others, and contribute to long-term strategic decisions, making it suitable for experienced engineers seeking growth toward Principal-level impact.

Responsibilities

Lead the design, development, and maintenance of backend services and APIs, ensuring high scalability, reliability, and performance.; Build and maintain data pipelines for batch and streaming workloads.; Deploy and manage applications in containerized and orchestrated environments.; Integrate services with data storage systems, relational databases, and data platforms.; Contribute to CI/CD pipelines and automated deployment processes.; Participate in system design and architecture discussions, influencing platform standards and long-term technical strategy.; Collaborate with data engineers, platform teams, and cross-functional stakeholders to deliver integrated platform solutions.; Monitor, support, and continuously improve production services and platform reliability.

Requirements

Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field.; 5–10+ years of experience in backend development, platform engineering, cloud-native systems, or data engineering, with increasing responsibility in design, architecture, or platform ownership.; Strong programming experience in Python and backend frameworks (FastAPI, Flask, Django) or equivalent.; Proven experience designing and implementing RESTful APIs and microservices.; Hands-on experience with Docker and exposure to Kubernetes or equivalent orchestration platforms.; Familiarity with cloud platforms (AWS preferred or similar).; Experience with data processing systems such as Spark, Kafka, Hive, or similar frameworks.; Experience with relational databases (PostgreSQL, MySQL, or equivalent).; Strong understanding of distributed systems principles, scalability, reliability, and performance.; Strong problem-solving, analytical, and ability to influence technical decisions and platform architecture.

Nice to have

Experience contributing to enterprise-level data platforms or analytics infrastructure.; Experience with streaming systems or event-driven architectures.; Familiarity with data warehouse, ELT/ETL, or big data ecosystem patterns.; Proven experience operating production services at scale, including observability and performance monitoring.; Exposure to manufacturing, industrial, or IoT data domains.; Experience providing technical guidance or mentorship to engineers.; Familiarity with high-throughput or real-time data systems and cloud-native observability tools.