Data & Analytics Engineer

The Enterprise Data & Analytics (EDA) organization at NetApp is seeking a highly motivated Data & Analytics Engineer (IC2) to help build and support enterprise data analytics automation and AI-powered solutions. This role will partner with business and IT stakeholders to develop semantic models data products dashboards intelligent automation and AI-enabled applications that drive data-driven decision-making across Operations.

The ideal candidate will have foundational experience in analytics data engineering Power BI SQL cloud data platforms and emerging AI technologies including Generative AI Machine Learning (ML) Large Language Models (LLMs) and Agentic AI frameworks. Exposure to Supply Chain Procurement Logistics Manufacturing or Enterprise Operations analytics is a plus.

Key Responsibilites

1. Develop and maintain Power BI semantic models dashboards and reports.
2. Perform data extraction cleansing transformation validation and analysis.
3. Build and support data pipelines integrations and ETL/ELT processes across enterprise platforms.
4. Assist in developing AI-enabled solutions leveraging LLMs Generative AI machine learning and intelligent automation.
5. Support the development of AI agents conversational analytics and agentic workflows that improve productivity and decision-making.
6. Ensure data quality governance reliability and consistency across analytics solutions.
7. Collaborate with business stakeholders to gather requirements and translate them into scalable analytics solutions.
8. Document business processes data flows technical specifications and solution designs.
9. Explore emerging technologies in Data Engineering GenAI Agentic AI ML and Cloud Analytics to identify business use cases.
10. Contribute to building reusable analytics automation and AI assets for enterprise-wide adoption.

1. 13 years of experience in Data Analytics Business Intelligence Data Engineering or AI-related projects.
2. Hands-on experience with Power BI development dashboard design DAX Power Query and semantic modelling.
3. Strong SQL and data analysis skills with exposure to Snowflake Oracle Databricks or modern cloud data platforms.
4. Understanding of data modelling ETL/ELT pipelines data integration and data warehousing concepts.
5. Basic programming experience in Python SQL or similar languages.
6. Familiarity with Generative AI platforms such as Azure OpenAI Microsoft Copilot OpenAI APIs or equivalent technologies.
7. Understanding of Large Language Models (LLMs) prompt engineering Retrieval-Augmented Generation (RAG) embeddings vector databases and knowledge search concepts.
8. Exposure to AI/ML concepts including supervised learning predictive analytics recommendation systems and data science fundamentals.
9. Understanding of Agentic AI concepts AI agents orchestration frameworks MCP tool calling or workflow automation is desirable.
10. Knowledge of REST APIs automation technologies Power Automate Office Scripts or similar tools.
11. Understanding of data governance data quality security and metadata management principles.

Analytical & Business Skills

1. Strong analytical problem-solving and critical-thinking abilities.
2. Ability to analyse structured and unstructured data to generate actionable insights.
3. Ability to understand business requirements and translate them into technical solutions.
4. Strong attention to detail with a focus on data accuracy and quality.
5. Exposure to Supply Chain Procurement Logistics Manufacturing or Operations analytics is an added advantage.
6. Curiosity and willingness to learn emerging AI ML and data technologies.

Collaboration & Communication

1. Strong verbal and written communication skills.
2. Ability to work effectively in cross-functional business and technical teams.
3. Strong collaboration and stakeholder engagement skills.
4. Ability to manage multiple priorities in a dynamic environment.
5. Ability to communicate technical concepts to business audiences and vice versa.

1. Bachelors or Masters degree in Computer Science Engineering Information Systems Data Science Analytics AI/ML or a related field.
2. Minimum 2 years of relevant industry experience required.
3. Experience in Data Analytics Business Intelligence Data Engineering Cloud Analytics AI/ML or Generative AI solutions preferred.