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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and maintain scalable ETL/ELT and real-time streaming data pipelines on Google Cloud Platform using services such as Cloud Dataflow, Cloud Composer, BigQuery, and Cloud Pub/Sub.
Architect and manage data lake, data warehouse, and analytics solutions including data modeling, partitioning, clustering, and lifecycle policies with emphasis on cost efficiency and security.
Implement automated data quality checks, monitoring, and troubleshooting, while supporting self-service analytics via data cataloging and documentation.
Minimum Requirements
Bachelor's degree in Computer Science, Engineering, or a related field.
2+ years of experience in data engineering or related roles with at least 2+ years specifically on Google Cloud Platform.
Hands-on experience with GCP services: BigQuery, Cloud Dataflow, Cloud Composer (Apache Airflow), Cloud Storage, Cloud Pub/Sub, Dataform/dbt, and Cloud Functions.
Proficiency in Python/Java and SQL, knowledge of Spark/Beam, experience with both RDBMS and NoSQL databases, and usage of version control (Git) and CI/CD pipelines.
Ideal Candidate Profile
Experienced in designing and optimizing scalable cloud-native data pipelines and architectures, specifically on GCP.
Well-versed in data modeling, dimensional modeling, and building complex analytical data platforms with a focus on performance and cost optimization.
Familiar with infrastructure as code tools (Terraform or equivalent) and skilled in implementing data governance, security, and monitoring frameworks.