Sr. Data Engineer
Redolent
Job Title: Data Engineer
Location: Bethpage, NY
Key Responsibilities:
• Data Pipeline Design and Implementation:
Develop and implement scalable and reliable data pipelines using GCP services like BigQuery, Dataflow, Cloud Storage, and Composer.
• Medallion Architecture Implementation:
Design and implement the bronze, silver, and gold layers within the Medallion architecture to organize and process data effectively.
• Data Storage and Processing:
Implement data storage solutions and optimize data processing workflows using appropriate GCP tools and technologies. • Data Quality and Security:
Ensure data quality, integrity, and security throughout the data lifecycle, including data validation, cleansing, and access control.
• Collaboration and Communication:
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver effective data solutions. • Monitoring and Maintenance:
Monitor and maintain the health of the data infrastructure, troubleshoot and resolve data-related issues, and ensure optimal performance.
• Staying Updated:
Keep up to date with the latest GCP features, data engineering best practices, and advancements in data architecture. • Data Governance:
Implement data governance strategies to ensure compliance with industry standards and best practices. Skills and Qualifications:
• GCP Expertise:
Strong knowledge of Google Cloud Platform (GCP) services, including BigQuery, Dataflow, Cloud Storage, and Composer.
• Medallion Architecture:
Solid understanding of the Medallion architecture principles and best practices.
• Data Engineering:
Proven experience in data engineering, including data warehousing, ETL processes, and data modelling.
• Programming Languages:
Proficiency in programming languages like Python, SQL, and potentially Apache Beam (for Dataflow). • Problem-Solving:
Strong problem-solving and analytical skills to troubleshoot and resolve data-related issues. • Communication:
Excellent communication and collaboration skills to work effectively with various teams.
• Cloud Architecture:
Knowledge of cloud architecture best practices, including scalability, reliability, and security.
• Data Modelling:
Experience with data modelling techniques and tools. In essence, a GCP Data Engineer focused on Medallion Architecture is a key player in building and managing data platforms on GCP, leveraging the Medallion pattern to ensure data quality, efficiency, and accessibility for various data consumers.
Location: Bethpage, NY
Key Responsibilities:
• Data Pipeline Design and Implementation:
Develop and implement scalable and reliable data pipelines using GCP services like BigQuery, Dataflow, Cloud Storage, and Composer.
• Medallion Architecture Implementation:
Design and implement the bronze, silver, and gold layers within the Medallion architecture to organize and process data effectively.
• Data Storage and Processing:
Implement data storage solutions and optimize data processing workflows using appropriate GCP tools and technologies. • Data Quality and Security:
Ensure data quality, integrity, and security throughout the data lifecycle, including data validation, cleansing, and access control.
• Collaboration and Communication:
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver effective data solutions. • Monitoring and Maintenance:
Monitor and maintain the health of the data infrastructure, troubleshoot and resolve data-related issues, and ensure optimal performance.
• Staying Updated:
Keep up to date with the latest GCP features, data engineering best practices, and advancements in data architecture. • Data Governance:
Implement data governance strategies to ensure compliance with industry standards and best practices. Skills and Qualifications:
• GCP Expertise:
Strong knowledge of Google Cloud Platform (GCP) services, including BigQuery, Dataflow, Cloud Storage, and Composer.
• Medallion Architecture:
Solid understanding of the Medallion architecture principles and best practices.
• Data Engineering:
Proven experience in data engineering, including data warehousing, ETL processes, and data modelling.
• Programming Languages:
Proficiency in programming languages like Python, SQL, and potentially Apache Beam (for Dataflow). • Problem-Solving:
Strong problem-solving and analytical skills to troubleshoot and resolve data-related issues. • Communication:
Excellent communication and collaboration skills to work effectively with various teams.
• Cloud Architecture:
Knowledge of cloud architecture best practices, including scalability, reliability, and security.
• Data Modelling:
Experience with data modelling techniques and tools. In essence, a GCP Data Engineer focused on Medallion Architecture is a key player in building and managing data platforms on GCP, leveraging the Medallion pattern to ensure data quality, efficiency, and accessibility for various data consumers.
Vacancy posted 2 days ago
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