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Posted on: 16 Mar 2024
Job Location: Pennington, US
Job Description:
Job Title: Cloud Data Engineer (Google Cloud Platform)
We are seeking a skilled and motivated Cloud Data Engineer to join our team and play a key role in designing, building, and maintaining our cloud-based data infrastructure using Google Cloud Platform. If you are passionate about cloud-based data solutions and data engineering, we invite you to apply and be part of our exciting journey.
Job Summary:
As a Cloud Data Engineer, you will be responsible for developing and optimizing our cloud-based data solutions, enabling the organization to collect, store, and analyze data efficiently. You will work closely with cross-functional teams to support data integration, transformation, and analytics, contributing to the success of our data-driven initiatives.
Key Responsibilities:
Data Architecture: Design and implement robust, scalable, and cloud-based data architectures, leveraging Google Cloud Platform.
Data Integration: Develop ETL (Extract, Transform, Load) pipelines to extract data from various sources, transform it for analysis, and load it into data warehouse.
Data Modeling: Create and maintain data models that support business intelligence, analytics, and reporting needs.
Data Quality: Implement data cataloging, metadata management, quality checks and ensure data accuracy, consistency, and completeness using services like Data Plex.
Cloud Services: Utilize cloud services, such as Google Cloud Storage, Composer, Big Query and workflow management services like Apache Airflow, to create and manage data pipelines effectively.
Data Security: Implement security and compliance measures to protect sensitive data and ensure data privacy using encryption (at rest, in transit and in use), data masking etc.
Performance Optimization: Identify and resolve performance bottlenecks, ensuring optimal data processing and storage.
Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and provide data support for analytics and reporting.
Documentation: Maintain comprehensive documentation of data pipelines, processes, and systems for knowledge sharing and troubleshooting.
Automation: Implement automation and monitoring tools to streamline data operations and detect and resolve issues proactively.
Qualifications:
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