Google Cloud Platform SPANNER DATA ENGINEER

SUNRAY INFORMATICS

East Brunswick, United States

about 2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

dice.com

Tech stack

Airflow Data Analysis Big Data BigQuery Cloud Computing Cloud Storage Data as a Services Data Architecture Information Engineering Extract Transform Load (ETL) Data Warehousing Database Queries

+18 more

Document Management Systems Data Flow Control Github Apache Hadoop Python (Programming Language) NoSQL Performance Tuning Query Optimization Cloudera Data Streaming Google Cloud Apache Spark Build Server Git Information Technology Software Version Control Data Pipelines Serverless Computing

Job description

THE FOLLOWING SKILLS ARE A MUST AS PER NOTE: Google Cloud Platform Spanner, Firestore, Python tech stack along with other standard Google Cloud Platform Services, Cloud Workflow, and BigQuery

Requirements

OVERALL EXPEREINCE A MINIMUM OF 10-12YRS+ MUST HAVE SOME TELECOM DOMAIN EXPEREINCE., * 12+ years of experience in data engineering with at least 5+ years on Google Cloud Platform (Google Cloud Platform).

Solid understanding of network/telecom domains, including relevant data types and use cases.
Expertise in Google Cloud Platform tools, including:
BigQuery for schema design, partitioning, clustering, query optimization, cost governance, data warehousing and analytics
Dataproc for managing Apache Spark and Hadoop clusters
Airflow for orchestration of workflows and pipelines
Data streaming with Python
Strong experience in Apache Spark and Hadoop ecosystems.
Production experience with Cloud Spanner schema design, interleaving, transaction patterns, and performance tuning
Solid understanding of Google Cloud Platform data services: Dataflow, Pub/Sub, Cloud Storage, Dataproc, Cloud Composer
Experience with Cloud Workflows for serverless orchestration
Hands-on experience with Firestore (Native mode preferred) for NoSQL/document storage patterns
Strong SQL skills and understanding of data warehousing concepts
Experience with CI/CD pipelines (Cloud Build, GitHub Actions) and version control (Git)
Ability to design, develop, and optimize ETL/ELT pipelines for large-scale data.
Hands-on experience in data modeling and data architecture design.
Strong problem-solving skills and ability to redesign existing solutions if needed.
Excellent communication and interpersonal skills to collaborate with both technical and business teams.
Bachelor s Degree in Computer Science, Engineering, or a related field; OR equivalent combination of education and relevant experience.