Experience:

• 4–6 years of professional experience in data engineering, ML engineering, or applied AI roles
• Proven track record of delivering at least 2–3 production-grade data or AI projects end-to-end

Responsibilities:

• Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data ingestion
• Develop and optimize data products using medallion architecture on platforms like Databricks
• Implement data quality, lineage, and governance controls
• Build, deploy, and monitor machine learning models including classification, regression, forecasting, and anomaly detection
• Develop GenAI and LLM-powered solutions including RAG pipelines and prompt engineering
• Operationalize ML models through MLOps practices including CI/CD, model versioning, drift monitoring, and automated retraining
• Deploy and manage data and AI workloads on cloud platforms such as Azure, AWS, or GCP

Additional responsibilities:

• Work within a global team ecosystem

Nice to have:

• Experience with enterprise ERP data and integration patterns such as CDC, IDoc, OData, APIs
• Exposure to supply chain, procurement, and logistics analytics use cases including spend, demand forecasting, and supplier risk
• Familiarity with Copilot Studio or Agentic AI frameworks

More skills:

ETL/ELT pipelines, SAP S/4HANA, Oracle, Salesforce, third-party APIs, enterprise data lakes/lakehouses, Databricks, data quality, data lineage, data governance, Purview, Alation, Unity Catalog, ML models, classification, regression, forecasting, anomaly detection, Python, PySpark, scikit-learn, TensorFlow, PyTorch, LLM-powered solutions, Pinecone, Azure AI Search, CI/CD for ML, Azure ML, SageMaker, Vertex AI, Azure, AWS, GCP, ADF, Glue, Lambda, Functions, Kubernetes

Other:

• Full-time exempt position
• Business function: Artificial Intelligence & Machine Learning
• Work location: Bangalore PTP Office (IBP)
• Sandisk values diversity and inclusion and is committed to providing accommodations for applicants with disabilities