Job Title: Senior Data Engineer –Google Cloud Platform
Experience: 12–14 Years
Job Type: Contract
Location: [Remote / Hybrid / Onsite – TBD]
Job Summary
We are looking for an experienced Senior Data Engineer with strong hands-on expertise in Google Cloud Platform (Google Cloud Platform) to design, develop, and maintain scalable cloud-based data engineering and analytics solutions.
The ideal candidate will have 12–14 years of overall IT experience with strong experience in Data Engineering, Google Cloud Platform, data warehousing, ETL/ELT, SQL, Python, and large-scale data processing.
The candidate should have extensive hands-on experience with core Google Cloud Platform data services such as BigQuery, Dataflow, Cloud Storage, Pub/Sub, and Cloud Composer/Airflow and should be capable of designing and optimizing enterprise-level data pipelines.
Mandatory Skills
Google Cloud Platform – Strong / Mandatory
· Strong hands-on experience with Google Cloud Platform (Google Cloud Platform).
· Strong experience with BigQuery.
· Hands-on experience with Dataflow / Apache Beam.
· Experience with Google Cloud Storage (GCS).
· Experience with Cloud Composer / Apache Airflow.
· Experience with Pub/Sub.
· Strong understanding of Google Cloud Platform data architecture and cloud services.
Key Responsibilities
· Design, develop, and maintain scalable data pipelines on Google Cloud Platform.
· Build end-to-end ETL/ELT workflows for structured and unstructured data.
· Develop complex data transformations using Python and SQL.
· Design and optimize data warehouse solutions using BigQuery.
· Develop and maintain data processing pipelines using Dataflow / Apache Beam.
· Implement data ingestion and storage solutions using Google Cloud Storage (GCS).
· Develop workflow orchestration using Cloud Composer / Apache Airflow.
· Build batch and real-time data processing solutions using appropriate Google Cloud Platform services.
· Work with Pub/Sub for event-driven and streaming data pipelines.
· Optimize BigQuery queries, data pipelines, and Google Cloud Platform resources for performance and cost.
· Implement data quality, validation, reconciliation, and error-handling processes.
· Troubleshoot complex data pipeline and production issues.
· Design data models for analytical and reporting requirements.
· Collaborate with Data Architects, Data Scientists, Analysts, Developers, and business stakeholders.
· Participate in technical design discussions, code reviews, testing, deployment, and production support.
· Follow best practices for cloud security, scalability, reliability, and data governance.
· Mentor junior and mid-level data engineers and provide technical guidance.
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