Senior Data Infrastructure Architect

1 week ago

Singapore beBeeDataEngineer Full time $120,000 - $180,000
Data Engineer

As a seasoned data engineer, you will design, build, and maintain robust, scalable data infrastructure. You will architect and develop end-to-end internal automation solutions using big data technologies.

You should have a proven track record of delivering data pipeline solutions and architecture. Understanding business requirements is essential to building reliable data infrastructure.

Responsibilities
  • Design, build, and maintain robust, scalable data infrastructure, including real-time and batch ETL/ELT data pipelines, using orchestration tools like Apache Airflow
  • Develop and manage the organization's data lake and data warehouse, implement sophisticated data models and applying modern data transformation practices with tools like dbt
  • Automate and optimize data processes by integrating disparate systems, APIs, and third-party services to ensure seamless data flow and synchronization
  • Establish and enforce best practices for data governance, quality, and lineage, implementing automated monitoring and alerting to ensure system reliability
Requirements
  • Minimum Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or equivalent is preferred
  • At least 5 years of relevant tech, app development or data engineering working experience
  • Deep understanding of software engineering principles, system architecture, and object-oriented design, with proven experience building production-grade applications
  • Expert proficiency in Python, including experience with data manipulation libraries (e.g., Pandas, NumPy), and frameworks for web scraping (e.g., Scrapy) or AI/ML (e.g., TensorFlow, PyTorch)
  • Proficiency with workflow orchestration tools like Apache Airflow for scheduling and managing complex data pipelines
  • Experience with data transformation tools like dbt, and a strong understanding of modern ETL/ELT design patterns and principles
  • Strong experience in data modeling techniques (conceptual, logical, physical) and designing scalable data warehouse schemas
  • Extensive hands-on experience with a major cloud platform (AWS, GCP, or Azure), including its native data services, compute, and storage solutions
  • Strong command of DevOps practices, including building and managing CI/CD pipelines and using infrastructure as code (IaC) tools like Terraform or CloudFormation
  • Advanced SQL skills and experience designing and optimizing relational databases (e.g., PostgreSQL, Oracle, SQL Server) and data warehouse schemas
  • Practical experience with containerization and orchestration technologies such as Docker and Kubernetes for deploying and scaling applications
  • Experience in building AI agents or developing solutions using Generative AI models and frameworks (e.g., LangChain, LlamaIndex) is a significant plus
  • Excellent ability to translate complex technical concepts into clear business context for stakeholders at all levels
  • Strong ownership mindset with the ability to work independently and manage projects from inception to completion

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