Sr Cloud Data Engineer, SMAI

Micron Technology, Inc; Hyderabad; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Micron Technology, Inc is looking for a Sr Cloud Data Engineer in Hyderabad, India, to enhance its data platforms and AI capabilities. The role requires collaboration with various teams to develop scalable data architectures that support advanced analytics and AI.

The ideal candidate has over 5 years in data engineering and experience with cloud solutions like AWS and Azure. The position includes responsibilities for building high-quality data pipelines as well as ensuring data governance and compliance.

Qualifications

• 5+ years of experience in data engineering or analytics solutions.
• Proficient in developing ETL processes using modern tools.
• Strong understanding of cloud platforms and data management.

Responsibilities

• Design and scale Micron’s data platforms and AI-ready data foundations.
• Collaborate with data scientists to enable advanced analytics.
• Build and run scalable data pipelines for AI and business systems.

Skills

Data Engineering

ETL/ELT Processes

Cloud Solutions (AWS/Azure/GCP)

Big Data Processing

SQL

Python

Data Governance

Communication Skills

Tools

Apache Ni-Fi

Snowflake

Spark

Job description

Req. ID: JR98220 – Sr Cloud Data Engineer, SMAI

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

As a Sr. Data Engineer at Micron Technology Inc., you will be a key member of a multi‑functional team responsible for developing and scaling Micron’s data platforms and AI‑ready data foundations in cloud. You will collaborate closely with data scientists, Architects, AI engineers, product teams, and business stakeholders to enable advanced analytics, machine learning, and Generative AI use cases across manufacturing, supply chain, and business systems.

You will design, build, and operate high‑quality, governed, and scalable data pipelines that power AI models, GenAI applications, and enterprise insights.

Responsibilities and Tasks

• Understand the Business Problem and the Relevant Data and AI Use cases
  • Maintain a deep understanding of business strategy, operational workflows, and AI/ML use cases
  • Translate business, analytics, and AI/ML requirements into scalable data architecture and pipelines
  • Identify and evaluate structured, semi‑structured, and unstructured data sources relevant to predictive analytics, optimization, and GenAI
  • Develop conceptual and logical data models optimized for feature engineering and model consumption
  • Define data quality, lineage, and observability objectives required for reliable AI and ML outcomes
  • Act as a domain expert for data availability, AI readiness, and reporting options
• Architect AI‑Ready Data Management Systems
  • Select and design data platforms (Big Data, OLTP, OLAP, Lakehouse) that support analytics, ML training, and inference workloads
  • Design and implement optimized data structures for model training, feature stores, and real‑time inference
  • Enable scalable storage and processing platforms (e.g., Google Cloud Platform (GCP), Snowflake, Azure, cloud data platforms, SQL engines) for AI workloads
  • Design data retention, archiving, and lifecycle strategies aligned to AI model governance and compliance
• Develop, Automate, and Orchestrate an Ecosystem of ETL Processes for AI & Analytics
  • Build and orchestrate batch, streaming, and near‑real‑time pipelines to support AI/ML and GenAI applications
  • Implement robust transformation pipelines to support feature engineering, embeddings, and model inputs
  • Enable ingestion and processing of unstructured data (logs, text, sensor data) for LLMs and sophisticated analytics
  • Optimize pipelines for performance, scalability, and cost across large‑volume AI datasets
  • Implement automation, monitoring, and alerting to ensure pipeline reliability for AI workloads
• Prepare and Serve Data for AI and Advanced Analytics
  • Partner with data scientists and ML engineers to enable:
    • Feature creation and reuse
    • Training, validation, and inference datasets
    • Feedback loops for model performance
  • Develop reusable, governed data assets for AI experimentation and production
  • Implement standards for data versioning, reproducibility, and audit‑ability.
  • Ensure datasets meet quality and consistency standards required for enterprise‑grade AI solutions
• Enable Generative AI (GenAI) & Sophisticated AI Use Cases
  • Build and lead data workflows that support Generative AI use cases, including:
    • Large Language Models (LLMs)
    • Vector databases and embedding pipelines
    • Retrieval‑Augmented Generation (RAG) architectures
  • Enable secure and compliant access to enterprise data for GenAI applications
  • Support timely development and model grounding by ensuring accurate, governed data retrieval
  • Collaborate with AI platform and MLOps teams to operationalize AI and GenAI solutions at scale
• Governance, Security, and Responsible AI
  • Ensure data pipelines align with enterprise security, privacy, and governance standards
  • Implement lineage, metadata management, and access controls to support Responsible AI
  • Partner with platform and compliance teams to ensure AI data usage aligns with corporate policies
• Continuous Improvement and Innovation
  • Evaluate and adopt emerging AI, GenAI, and data engineering technologies
  • Drive standardization and standards for AI‑ready data platforms
  • Mentor engineers on AI data patterns, effective processes, and scalable builds
  • Chip in to AI roadmap discussions and architecture decisions

Qualifications and Experience

• 5+ years developing, delivering, and/or supporting data engineering, sophisticated analytics or business intelligence solutions
• Experience working with multiple operating systems (e.g., MS Office, Unix, Linux, etc.)
• Experienced in developing ETL/ELT processes using Apache Ni‑Fi and Snowflake
• Experienced in cloud‑based solutions using AWS/AZURE/GCP
• Significant experience with big data processing and/or developing applications and data sources via Spark, etc.
• Understanding of how distributed systems work
• Familiarity with software architecture (data structures, data schemas, etc.)
• Strong working knowledge of databases (Oracle, MSSQL, etc.) including SQL and NoSQL
• Strong mathematics background, analytical, problem solving, and interpersonal skills
• Strong communication skills (written, verbal and presentation)
• Experience working in a global, multi‑functional environment
• Minimum of 2 years’ experience in any of the following: at least one high‑level client, object‑oriented language (e.g., C#, C++, JAVA, Python, Perl, etc.); at least one or more web programming language (PHP, MySQL, Python, Perl, JavaScript, ASP, etc.); one or more Data Extraction Tools (SSIS, Informatica etc.)
• Software development
• Ability to travel as needed

Job Profile(s): Data Engineer 3A

Relocation level: (TBD)

EEO Statement

Micron is proud to be an equal‑opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.