Role : Google Cloud Platform Spanner Data Engineer
Location: Dallas, TX
Duration: 12 Months
MOI : Telephonic & WebCam
Primary Skills: Google Cloud Platform Spanner, Firestore, Python tech stack, along with other standard Google Cloud Platform Services, Cloud Workflow, and BigQuery.
Need Candidates with at least 10 years of Experience. This is a 100% Onsite role.
3 Rounds of Interview
Candidates must have Telecom Domain Experience.
THE FOLLOWING SKILLS ARE A MUST AS PER MANAGER S NOTE: Google Cloud Platform Spanner, Firestore, Python tech stack, along with other standard Google Cloud Platform Services, Cloud Workflow, and BigQuery
Key Responsibilities:
- Design and implement scalable data pipelines using Google Cloud Platform-native services (Dataflow, Dataproc, Pub/Sub, Cloud Composer/Airflow)
- Architect and optimize BigQuery datasets, tables, and queries for analytical workloads at scale
- Design and manage Cloud Spanner schemas for globally distributed, strongly consistent transactional data
- Build and maintain data models, transformations, and orchestration workflows using Cloud Workflows and related tools
- Develop backend data services and ETL/ELT scripts in Python
- Integrate and manage Firestore for real-time, document-oriented data use cases
- Implement data governance, lineage, and quality frameworks using tools like Data Plex or Data Catalogue
- Collaborate on infrastructure-as-code using Terraform for Google Cloud Platform resource provisioning
- Monitor pipeline health, optimize costs, and troubleshoot production issues
- Redesign and optimize existing data pipelines and architectures as needed to ensure high performance and scalability.
- Oversee the end-to-end data delivery process, from ingestion to transformation and reporting.
- Perform code reviews, enforce best practices, and ensure the quality and consistency of the codebase.
- Manage workflows and scheduling with tools like Apache Airflow to ensure smooth execution of pipelines.
- Use Google Cloud Platform technologies like Dataflow, Apache Beam, BigQuery, Dataproc, and other services for data transformation, storage, and analysis.
- Develop scalable solutions with Apache Spark, Hadoop, and other distributed systems on Google Cloud Platform.
- Monitor and optimize the performance of data pipelines and processes.
- Collaborate with DevOps and Cloud teams for CI/CD integration and infrastructure optimization.
- Provide mentorship to junior engineers and manage the team s performance effectively.
Required Skills and Experience:
- 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 optimise ETL/ELT pipelines for large-scale data.
- Hands-on experience in data modelling 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.
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