Staff Engineer, Data Management Engineering

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.

Job Description

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Join us to lead data-driven transformation, building scalable data pipelines, advanced analytics ecosystems, and AI/ML workflows. As a Staff Data & Analytics Engineer, you will define technical strategy, mentor teams, and deliver actionable insights that shape strategic business and sustainability initiatives.

Key Responsibilities:

• Design and optimize scalable ETL/ELT pipelines for structured and unstructured data.
• Build analytics-ready datasets, BI dashboards, and KPI reports (Power BI, Tableau).
• Develop and manage feature pipelines for ML training, deployment, and monitoring (MLOps).
• Implement data quality, lineage, and governance frameworks for reliability and compliance.
• Containerize workloads using Docker and Kubernetes; support CI/CD automation.
• Mentor junior engineers and participate in architecture reviews and strategic planning.
• Drive architecture reviews and long-term data strategy, ensuring alignment with business goals.

Qualifications

Required:

• 8+ years in data engineering/analytics, with 3+ years at staff or senior level.
• Expertise in Python (pandas, PySpark), SQL, and big data technologies (Spark, Kafka).
• Hands-on experience with MLOps platforms (MLflow, Kubeflow, SageMaker).
• Strong cloud experience (AWS, GCP, or Azure) with containerization (Docker, Kubernetes).
• Proven track record in leading teams and delivering scalable analytics & AI solutions.

Preferred:

• Familiarity with modern data stacks (Delta Lake, Iceberg) and real-time data pipelines (Kafka, Kinesis, Flink).
• Data storytelling expertise, including designing business KPIs and translating analytics into actionable insights.
• Experience with workflow orchestration tools like Apache Airflow, Dagster, or Prefect.
• Familiarity with big data technologies such as Spark, Kafka, or Flink.
• Knowledge of containerization best practices and CI/CD pipelines (e.g., Jenkins, GitHub Actions).
• Understanding of data governance frameworks and compliance (GDPR, CCPA).
• Prior experience in sustainability or ESG data analytics is a plus.

Skills:

• SQL – Advanced querying and optimization.
• Python – Data libraries like pandas, NumPy, and PySpark.
• ETL/ELT Concepts – Scalable pipeline design and orchestration.
• Data Visualization – Power BI, Spotfire, Tableau.
• Cloud Fundamentals – AWS, GCP, or Azure basics.
• Data Engineering & Analytics – Data modeling, pipeline optimization, and quality frameworks.
• MLOps Awareness – Understanding ML pipelines and model deployment tools.
• Collaboration & Communication – Work cross-functionally with teams.
• Analytical Thinking & Troubleshooting – Diagnose and resolve data issues effectively.

Additional Information

Why Join Us?

You’ll shape the future of data and AI strategy within an organization committed to innovation and sustainability. This is an opportunity to lead impactful, enterprise-scale data initiatives and influence how the company leverages data-driven intelligence to drive growth and efficiency.

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 jobs.accommodations@sandisk.com 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.

NOTICE TO CANDIDATES: Sandisk has received reports of scams where a payment is requested on Sandisk’s behalf as a condition for receiving an offer of employment. Please be aware that Sandisk and its subsidiaries will never request payment as a condition for applying for a position or receiving an offer of employment. Should you encounter any such requests, please report it immediately to Sandisk Ethics Helpline or email compliance@sandisk.com.