Engineer, Data Analytics Engineering

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.

Description

Essential and Duties Responsibilities

We are seeking an experienced Engineer to join the Data Analytics Engineering team responsible for building next-generation data platforms, AI-enabled solutions, and manufacturing analytics products. This role will focus on designing scalable data architectures, developing enterprise-grade data pipelines, enabling AI/ML workloads, and accelerating digital transformation across manufacturing operations. The ideal candidate combines strong data engineering expertise with practical experience in cloud platforms, big data technologies, and AI solution deployment.

Key Responsibilities

Build scalable data pipelines, data products, and cloud-based data platforms. Enable AI, Machine Learning, and Generative AI solutions through robust data engineering. Develop analytics, dashboards, and self-service data solutions for business users. Ensure data quality, governance, security, and operational excellence. Partner with stakeholders to solve business challenges using data and AI.

Required

• Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, Engineering, or related field, with 3-5 years of experience in Data Engineering, Analytics Engineering, or Data Platform development.
• Knowledge of cloud data technologies (Azure/AWS) and big data processing frameworks.
• Strong analytical, problem-solving, and communication skills.
• Strong programming skills in Python and SQL with proven experience building and maintaining ETL/ELT pipelines.
  
  

Preferred

• Experience with Databricks, Spark, Delta Lake, or Lakehouse architecture.
• Experience with AI/ML, Generative AI, or MLOps solutions.
• Experience in manufacturing, semiconductor, or industrial analytics environments.
  
  

Skills

Python, SQL, ETL/ELT, and Data Engineering Databricks, Spark, Delta Lake Azure/AWS Cloud Data Platforms AI/ML, Generative AI, and MLOps Data Governance, and Data Quality Analytics Dashboard Development (Power BI/Tableau

Additional Information

Sandisk thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.

Sandisk is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at [Confidential Information] to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.