SR ENGINEER, DATA,SMAI

1840 Micron Tech. OP India LLP; Hyderabad; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

1840 Micron Tech. OP India LLP in Hyderabad is looking for a Data Engineer to design and implement scalable data architectures on Google Cloud Platform. The ideal candidate will have strong experience in Python and SQL, with proficiency in building ETL pipelines using tools like BigQuery.

Your responsibilities will include optimizing queries for performance, ensuring data governance, and working closely with teams to translate business requirements into technical solutions. Apply now to be part of our innovative team!

Qualifications

• Strong experience in data architecture on Google Cloud Platform.
• Proven skills in Python, SQL, and PySpark.
• Experience with data migration strategies and ETL pipelines.

Responsibilities

• Design and implement data architectures on Google Cloud Platform.
• Optimize BigQuery queries for performance.
• Build and maintain ETL pipelines using GCP services.

Skills

Python

SQL

PySpark

Data governance

ETL/ELT pipelines

Tools

Google Cloud Platform (GCP)

BigQuery

GCS

Terraform

Cloud Build

Job description

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 strong 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 of data warehousing concepts.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.