Data & Analytics Engineer

NetApp; Bengaluru; Hybrid; INR 1,200,000 - 2,200,000; Full time

Job summary

NetApp is seeking a Data & Analytics Engineer (IC2) to build and support enterprise data, analytics, automation, and AI-powered solutions for Operations. The role partners with business and IT to deliver scalable data products and dashboards.

The ideal candidate has hands-on experience with Power BI, SQL, cloud data platforms, and emerging AI technologies including Generative AI, ML, LLMs, and agentic AI frameworks, with exposure to Supply Chain or Enterprise Operations analytics a plus.

Qualifications

• 1–3 years of experience in Data Analytics, BI, or Data Engineering.

Responsibilities

• Develop and maintain Power BI semantic models, dashboards, and reports.

Skills

Power BI development

SQL

Python

REST APIs

Data modeling

Data governance

Analytics

Education

Bachelor's or Master's in CS/Engineering/Analytics

Tools

Power BI

Snowflake

Oracle

Databricks

Azure OpenAI

OpenAI APIs

Microsoft Copilot

Power Automate

Job description

Own Every Moment at NetApp

At NetApp, your ideas power innovation. We lead in intelligent data infrastructure—delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud.

Own Every Moment at NetApp

At NetApp, your ideas power innovation. We lead in intelligent data infrastructure—delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud.

Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Join teams that innovate to elevate, drive results, and excel together across every function.

Job Summary

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

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

Technical Skills

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

Analytical & Business Skills

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

Collaboration & Communication

• Strong verbal and written communication skills.
• Ability to work effectively in cross‑functional business and technical teams.
• Strong collaboration and stakeholder engagement skills.
• Ability to manage multiple priorities in a dynamic environment.
• Ability to communicate technical concepts to business audiences and vice versa.

Education

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Data Science, Analytics, AI/ML, or a related field.
• Minimum 2 years of relevant industry experience required.
• Experience in Data Analytics, Business Intelligence, Data Engineering, Cloud Analytics, AI/ML, or Generative AI solutions preferred.

At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in‑office and/or in‑person expectations, which will be shared during the recruitment process.

Equal Opportunity Employer:

NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification.

Why You'll Thrive at NetApp

At NetApp, you won't wait for the perfect moment—you'll make it. The early planning, the extra thought, the bold idea that turns good into great: That's how our people operate and how we continue to push the boundaries of data infrastructure.

NetApp is the trusted partner for organizations transforming data into opportunity. As the only enterprise‑grade storage service natively embedded in Google Cloud, AWS, and Microsoft Azure, we empower customers to run everything from traditional workloads to enterprise AI with unmatched performance, resilience, and security.

We celebrate mold breakers, bold thinkers, and problem solvers. We reward initiative, impact, and ownership. We provide flexibility so you can balance professional ambition with your personal life. Here, differences are not just welcomed—they drive everything we do.

If you're ready to innovate, rise to the challenge, and own every moment - make your next move your best one.

AI Disclosure

For select roles, some stages of our hiring process may use artificial intelligence tools to help evaluate applications and candidate selection. These tools support—rather than replace—human decision‑making.