Sr Engineer, Data

Micron Technology, Inc; Hyderabad; On-site; INR 1,800,000 - 2,500,000; Full time

Job summary

Micron Technology, Inc. is seeking a Sr Engineer, Data to design and implement scalable data architectures on Google Cloud Platform, leveraging Snowflake and BigQuery. The role focuses on building end-to-end ETL/ELT pipelines, optimizing performance, and ensuring data governance across diverse sources.

You will work with Data Scientists, Analysts, and product teams to translate business needs into robust data solutions, including batch and real-time processing and CI/CD for data workflows.

Qualifications

• At least 5 years of experience in implementing scalable, reliable data architectures on Google Cloud Platform (GCP).
• Understand data models, warehouse structures, and data lake strategies using BigQuery, Snowflake, and GCS.
• Build cloud data warehouse solutions on Snowflake — dimensional models, virtual warehouses, clustering/micro-partition strategy, roles and row-level security — and integrate Snowflake within the broader GCP data ecosystem.
• Follow best practices for schema design, partitioning, and clustering for performance optimization.
• Very Strong Experience in Python, SQL, PySpark.
• Strong hands‑on expertise with Snowflake, including advanced SQL, performance and cost tuning, and secure data sharing.
• 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 and Snowflake.
• 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 and Snowflake 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.

Responsibilities

• At least 5 years of experience in implementing scalable, reliable data architectures on Google Cloud Platform (GCP).
• Understand data models, warehouse structures, and data lake strategies using BigQuery, Snowflake, and GCS.
• Build cloud data warehouse solutions on Snowflake — dimensional models, virtual warehouses, clustering/micro-partition strategy, roles and row-level security — and integrate Snowflake within the broader GCP data ecosystem.
• Follow best practices for schema design, partitioning, and clustering for performance optimization.
• Very Strong Experience in Python, SQL, PySpark.
• Strong hands‑on expertise with Snowflake, including advanced SQL, performance and cost tuning, and secure data sharing.
• 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 and Snowflake.
• 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 and Snowflake 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.

Skills

Python

SQL

PySpark

BigQuery

Snowflake

ETL/ELT pipelines

Cloud data architectures

CI/CD

Data governance

Data migration

Tools

Google Cloud Platform (GCP)

BigQuery

Snowflake

DataProc

Cloud Run

Cloud Functions

Pub/Sub

Cloud Composer

Job description

Req. ID: JR110973 Sr Engineer, Data

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.

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

• At least 5 years of experience in implementing scalable, reliable data architectures on Google Cloud Platform (GCP).
• Understand data models, warehouse structures, and data lake strategies using BigQuery, Snowflake, and GCS.
• Build cloud data warehouse solutions on Snowflake — dimensional models, virtual warehouses, clustering/micro-partition strategy, roles and row-level security — and integrate Snowflake within the broader GCP data ecosystem.
• Follow best practices for schema design, partitioning, and clustering for performance optimization.
• Very Strong Experience in Python, SQL, PySpark.
• Strong hands‑on expertise with Snowflake, including advanced SQL, performance and cost tuning, and secure data sharing.
• 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 and Snowflake.
• 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 and Snowflake 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

• Snowflake exposure or equivalent production experience across multi‑cloud data platforms.
• Basic working knowledge of the AI/ML tech stack (e.g., Vertex AI / ADK, model/data pipelines, embeddings, LLM integration) and how data engineering supports AI workloads.
• Basic front‑end exposure with Angular / React for building or supporting lightweight data applications and dashboards.
• Exposure to AI/ML data pipelines (Vertex AI / ADK).
• Experience with streaming frameworks (Kafka, Pub/Sub).
• Strong understanding of data warehousing concepts.

Job Profile(s)

Data Engineer 3

Relocation level: (TBD)

Before Getting Started

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