Senior /Staff Data & Cloud Platform Engineer
Hyderabad, TS, IN
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
Tools in this posting
- Python
- SQL
- AWS
- BigQuery
- Docker
- Google Cloud (GCP)
- Kubernetes
- Redshift
- S3
- Terraform
- Airflow
Source — Tool mentions in context
* Experience: 5+ years in data engineering, cloud engineering, platform engineering, DevOps, or infrastructure engineering. * Programming: Strong hands-on experience with Python, SQL, automation scripts, and cloud-native data services. * Cloud Platforms: Practical experience with GCP services such as Dataflow, Pub/Sub, Cloud Functions, BigQuery, Cloud Storage, IAM, and AWS services such as Glue, Lambda, S3, Redshift, IAM.
* Entity Extraction: Extract and normalize key identifiers such as Lot, Die, Wafer, Test, Flow, Product, and Step. * Cloud Landing Zones: Set up secure AWS, GCP, and on-prem landing targets for validation and analytics pipelines. * Infrastructure Automation: Provision infrastructure using Terraform, CI/CD, and Infrastructure-as-Code practices.
* Workflow Orchestration: Development and management of batch, event-driven, and scheduled workflows using Apache Airflow. * Cloud Data Platforms: Building data solutions using GCP and AWS services for ingestion, processing, storage, and analytics. * Schema & Metadata Management: Implementation of schema registries, schema evolution, version control, metadata capture, and lineage readiness.
* Manufacturing Data Modeling: Extraction and normalization of Lot, Die, Wafer, Test, Flow, Product, Step, and validation identifiers. * Multi-Cloud Architecture: Secure and scalable data platforms across AWS, GCP, and on-premises environments. * Infrastructure Automation: Cloud provisioning using Terraform, automation frameworks, reusable modules, and CI/CD practices.
* Programming: Strong hands-on experience with Python, SQL, automation scripts, and cloud-native data services. * Cloud Platforms: Practical experience with GCP services such as Dataflow, Pub/Sub, Cloud Functions, BigQuery, Cloud Storage, IAM, and AWS services such as Glue, Lambda, S3, Redshift, IAM. * Infrastructure & DevOps: Experience with Terraform, Kubernetes, Docker, CI/CD, cloud networking, IAM, and operational automation.
* AI / Analytics Platforms: Data foundations for AI/ML, analytics, knowledge platforms, digital thread, traceability, or governed data products. * Certifications: AWS, GCP, Kubernetes, Terraform, or data engineering certifications are preferred but not mandatory. Job Profile(s):
* Infrastructure Automation: Provision infrastructure using Terraform, CI/CD, and Infrastructure-as-Code practices. * Platform Operations: Support containerized workloads using Kubernetes, Docker, monitoring, logging, and operational controls. * Security & Cost Optimization: Implement IAM, RBAC, hybrid connectivity, access controls, and cost optimization for TB-scale data.
* Infrastructure Automation: Cloud provisioning using Terraform, automation frameworks, reusable modules, and CI/CD practices. * Container & Platform Engineering: Operation of containerized applications and platform workloads using Kubernetes and Docker. * Cloud Security & Governance: IAM, RBAC, data protection, service accounts, secrets management, and enterprise access controls.
* Cloud Platforms: Practical experience with GCP services such as Dataflow, Pub/Sub, Cloud Functions, BigQuery, Cloud Storage, IAM, and AWS services such as Glue, Lambda, S3, Redshift, IAM. * Infrastructure & DevOps: Experience with Terraform, Kubernetes, Docker, CI/CD, cloud networking, IAM, and operational automation. * Collaboration: Ability to partner with IT, AI, Data Science, Engineering, and manufacturing stakeholders to deliver reliable platform capabilities.
* Cloud Landing Zones: Set up secure AWS, GCP, and on-prem landing targets for validation and analytics pipelines. * Infrastructure Automation: Provision infrastructure using Terraform, CI/CD, and Infrastructure-as-Code practices. * Platform Operations: Support containerized workloads using Kubernetes, Docker, monitoring, logging, and operational controls.
* Multi-Cloud Architecture: Secure and scalable data platforms across AWS, GCP, and on-premises environments. * Infrastructure Automation: Cloud provisioning using Terraform, automation frameworks, reusable modules, and CI/CD practices. * Container & Platform Engineering: Operation of containerized applications and platform workloads using Kubernetes and Docker.
* Data Pipeline Engineering: Build scalable ingestion pipelines for structured, semi-structured, and engineering data sources. * Workflow Orchestration: Develop reliable batch, scheduled, and event-driven workflows using Apache Airflow and cloud-native services. * ETL / ELT Frameworks: Implement reusable pipeline patterns, transformations, incremental ingestion, and data quality checks.
* Data Pipeline Engineering: Design and operation of scalable ingestion pipelines, ETL/ELT frameworks, metadata-driven processing, and data quality validation. * Workflow Orchestration: Development and management of batch, event-driven, and scheduled workflows using Apache Airflow. * Cloud Data Platforms: Building data solutions using GCP and AWS services for ingestion, processing, storage, and analytics.
Job description
Req. ID:
JR109153 Senior /Staff Data & Cloud Platform Engineer (Evergreen)
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.
Responsibilities
* Data Pipeline Engineering: Build scalable ingestion pipelines for structured, semi-structured, and engineering data sources.
* Workflow Orchestration: Develop reliable batch, scheduled, and event-driven workflows using Apache Airflow and cloud-native services.
* ETL / ELT Frameworks: Implement reusable pipeline patterns, transformations, incremental ingestion, and data quality checks.
* Schema Management: Implement schema registry, schema versioning, schema evolution, and compatibility controls.
* Delta Detection: Build change detection and incremental refresh mechanisms for efficient large-scale data synchronization.
* Entity Extraction: Extract and normalize key identifiers such as Lot, Die, Wafer, Test, Flow, Product, and Step.
* Cloud Landing Zones: Set up secure AWS, GCP, and on-prem landing targets for validation and analytics pipelines.
* Infrastructure Automation: Provision infrastructure using Terraform, CI/CD, and Infrastructure-as-Code practices.
* Platform Operations: Support containerized workloads using Kubernetes, Docker, monitoring, logging, and operational controls.
* Security & Cost Optimization: Implement IAM, RBAC, hybrid connectivity, access controls, and cost optimization for TB-scale data.
* Cross-Functional Delivery: Partner with IT, TPG AI, SMAI, Data Science, Product Engineering, and platform teams.
Expertise
* Data Pipeline Engineering: Design and operation of scalable ingestion pipelines, ETL/ELT frameworks, metadata-driven processing, and data quality validation.
* Workflow Orchestration: Development and management of batch, event-driven, and scheduled workflows using Apache Airflow.
* Cloud Data Platforms: Building data solutions using GCP and AWS services for ingestion, processing, storage, and analytics.
* Schema & Metadata Management: Implementation of schema registries, schema evolution, version control, metadata capture, and lineage readiness.
* Incremental Data Processing: Development of delta detection, CDC-style processing, watermarking, and efficient refresh strategies.
* Manufacturing Data Modeling: Extraction and normalization of Lot, Die, Wafer, Test, Flow, Product, Step, and validation identifiers.
* Multi-Cloud Architecture: Secure and scalable data platforms across AWS, GCP, and on-premises environments.
* Infrastructure Automation: Cloud provisioning using Terraform, automation frameworks, reusable modules, and CI/CD practices.
* Container & Platform Engineering: Operation of containerized applications and platform workloads using Kubernetes and Docker.
* Cloud Security & Governance: IAM, RBAC, data protection, service accounts, secrets management, and enterprise access controls.
* Hybrid Cloud Connectivity: Networking, VPN, private connectivity, and secure integration between cloud and on-prem environments.
* Reliability & Cost Management: Monitoring, observability, performance tuning, troubleshooting, and optimization for TB-scale workloads.
Qualifications
* Education: Bachelor's degree in Computer Science, Data Engineering, Cloud Engineering, Information Systems, or related technical field.
* Experience: 5+ years in data engineering, cloud engineering, platform engineering, DevOps, or infrastructure engineering.
* Programming: Strong hands-on experience with Python, SQL, automation scripts, and cloud-native data services.
* Cloud Platforms: Practical experience with GCP services such as Dataflow, Pub/Sub, Cloud Functions, BigQuery, Cloud Storage, IAM, and AWS services such as Glue, Lambda, S3, Redshift, IAM.
* Infrastructure & DevOps: Experience with Terraform, Kubernetes, Docker, CI/CD, cloud networking, IAM, and operational automation.
* Collaboration: Ability to partner with IT, AI, Data Science, Engineering, and manufacturing stakeholders to deliver reliable platform capabilities.
* Proven ability to leverage AI‑assisted (vibe) coding techniques to improve efficiency or automate design and analysis methodologies
* Leverage AI tools to automate the tools and workflow
Applying Artificial Intelligence in workflows to improve build efficiency
Preferred Domain Exposure
* Industrial / Engineering Context: Semiconductor, NAND, product engineering, validation, manufacturing, reliability, quality, test, yield, or RCA data environments.
* AI / Analytics Platforms: Data foundations for AI/ML, analytics, knowledge platforms, digital thread, traceability, or governed data products.
* Certifications: AWS, GCP, Kubernetes, Terraform, or data engineering certifications are preferred but not mandatory.
Job Profile(s):
Product Development Engineer 3
Relocation level: (TBD)
Before Getting Started
Please review Micron’s Internal Job Application Policy on your regional PeopleNow Career Opportunities page before searching and applying for jobs. Note in particular that:
* Hiring managers may view your performance appraisals, original resume, transcripts or other performance-related documentation in your personal file. This information will be held in confidence.
* If you are selected to interview for a position, you must notify your direct supervisor before participating in the interview process.
As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on Benefits | Micron Technology, Inc
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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on careers.micron.com. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Hyderabad, TS, IN
* Platform Operations: Support containerized workloads using Kubernetes, Docker, monitoring, logging, and operational controls. * Security & Cost Optimization: Implement IAM, RBAC, hybrid connectivity, access controls, and cost optimization for TB-scale data. * Cross-Functional Delivery: Partner with IT, TPG AI, SMAI, Data Science, Product Engineering, and platform teams.
More source context
* Cloud Security & Governance: IAM, RBAC, data protection, service accounts, secrets management, and enterprise access controls. * Hybrid Cloud Connectivity: Networking, VPN, private connectivity, and secure integration between cloud and on-prem environments. * Reliability & Cost Management: Monitoring, observability, performance tuning, troubleshooting, and optimization for TB-scale workloads.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Aug 19, 2026
- Recorded sightings
- 44
- Last seen by us
- Oct 9, 2026
- Employer says posted
- Aug 17, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Report an errorSee how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.