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.

Job Roles & Responsibilities:
- Design and implement scalable, reliable data architectures on Google Cloud Platform (GCP).
- Define data models, warehouse structures, and data lake strategies using BigQuery and GCS.
- Establish best practices for schema design, partitioning, and clustering for performance optimization.
- Very Solid Experience in Python, SQL, PySpark.
- Build and maintain end-to-end ETL/ELT pipelines using GCP services such as: BigQuery, WorkFlow, Dataproc, Cloud Run , Cloud Functions, Pub/Sub, Cloud Composer.
- Develop batch and real-time data processing pipelines.
- Implement CI/CD pipelines for data workflows using Cloud Build / Terraform.
- Ensure high performance, reliability, and fault tolerance in pipelines.




- Design and execute data migration strategies from on-prem / legacy systems to GCP.
- Integrate multiple data sources (structured, semi-structured, unstructured).
- Handle large-scale data ingestion using streaming and batch approaches.
- Implement data validation, monitoring, and quality checks.
- Ensure adherence to data governance, security, and compliance policies.
- Build frameworks for data lineage and observability - Cloud Monitoring / Logging and BigQuery audit logs.
- Optimize BigQuery queries, storage costs, and pipeline performance, Tune Spark/PySpark jobs in Dataproc environments.
- Implement query optimization and cost-efficient designs.
- Work closely with: Data Scientists, Data Analysts, Product & Business teams
- Translate business requirements into scalable technical solutions

Nice To Have:
- Exposure to AI/ML data pipelines (Vertex AI / ADK).
- Experience with streaming frameworks (Kafka, Pub/Sub).
- Strong understanding

📌 Sr Engineer, Data,Smai (Hyderabad)
🏢 Micron
📍 Hyderabad