Senior Cloud Architect – Data Engineering

9 hours ago

Calamba, Calabarzon, Philippines beBeeCloud Full time ₱1,200,000 - ₱2,000,000
Job Overview

Our organization is seeking a skilled Senior Cloud Data Engineer to play a critical role in designing, building, and maintaining our data infrastructure to support analytics, reporting, and business intelligence.

The ideal candidate will have a strong background in cloud-based (AWS) data engineering, automation, and DevOps practices, looking to work in a fast-paced, data-driven environment.

We are looking for an individual who can design, develop, and maintain scalable data pipelines using AWS services such as S3, Glue, Lambda, and RDS. Additionally, the successful candidate should be able to build robust ETL processes to ingest, transform, and store data efficiently.

Responsibilities
  • Design and Develop Scalable Data Pipelines: Utilize AWS services like S3, Glue, Lambda, and RDS to create efficient data pipelines.
  • Build Robust ETL Processes: Ingest, transform, and store data efficiently using ETL best practices.
  • Manage and Optimize Relational Databases: Ensure relational databases are optimized to meet business needs.
  • Ensure High-Quality Data: Validate, monitor, and govern data to ensure high quality.
  • Develop Scripts and Automation Tools: Create scripts and tools using Python, SQL, and Bash to streamline data processes and workflows.
  • Support Business Users: Ensure data is structured and accessible in reporting tools like Tableau or Metabase.
  • Implement Best Practices: Follow version control, testing, and deployment best practices for data pipelines.
Key Skills And Experience
  • Proven Experience: Proven experience in data engineering, working with cloud-based data platforms (AWS).
  • Python Proficiency: Strong proficiency in Python for data processing and automation.
  • SQL Experience: Experience with SQL and database management (PostgreSQL, MySQL, or similar).
  • AWS Services: Hands-on experience with AWS services such as Glue, S3, Lambda, and RDS.
  • ETL/ELT Best Practices: Understanding of ETL/ELT best practices and experience building data pipelines.
  • Data Visualization: Experience with data visualization and BI tools such as Tableau or Metabase.
  • Infrastructure-as-Code: Experience with infrastructure-as-code tools (Terraform, CloudFormation) for data infrastructure automation.
  • Data Quality Focus: Strong focus on data quality, security, and governance.

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