Data Architect

1 day ago

Manila, National Capital Region, Philippines Nezda Global Full time ₱1,500,000 - ₱3,000,000 per year

About the Role

We're looking for a
Data Architect
who can design, implement, and maintain scalable data systems that drive business insight and innovation. You'll be responsible for defining the data strategy, ensuring the reliability of data platforms, and guiding development teams in best practices for data modeling and governance.

Key Responsibilities

  • Design and implement enterprise-wide data architecture solutions aligned with organizational goals.
  • Develop conceptual, logical, and physical data models that meet business requirements.
  • Lead the design of data warehouses, data lakes, and ETL pipelines.
  • Collaborate with data engineers, analysts, and business stakeholders to ensure high data quality and accessibility.
  • Define and enforce data governance, security, and compliance standards.
  • Evaluate emerging tools, technologies, and frameworks for data storage, integration, and analytics.
  • Optimize performance and scalability of data infrastructure.

Must-Have Qualifications

  • Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
  • 8+ years of experience in data architecture, data engineering, or related roles.
  • Proven expertise in
    SQL
    and at least one programming language (Python, Java, Scala, etc.).
  • Strong experience with
    data modeling tools
    (e.g., ERwin, PowerDesigner).
  • Deep understanding of
    ETL processes
    ,
    data warehousing
    , and
    data integration frameworks
    .
  • Hands-on experience with
    cloud data platforms
    such as
    AWS Redshift, Azure Synapse, GCP BigQuery
    , or
    Snowflake
    .
  • Solid grasp of
    data governance
    ,
    master data management (MDM)
    , and
    metadata management
    .

Good-to-Have

  • Experience in
    real-time data streaming
    using Kafka or similar.
  • Familiarity with
    data lakehouse architectures
    and tools like
    Databricks
    .
  • Exposure to
    AI/ML model data pipelines
    .
  • Certifications in AWS, Azure, or GCP data services.

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