Data Architect

2 weeks ago

Quezon City, Philippines HRTX Full time

Responsibilities)

  • Design, implement, and maintain scalable and efficient data architectures to support AI and automation projects.
  • Collaborate with data scientists, AI researchers, and engineers to ensure data availability and quality for AI model training and deployment.
  • Develop and optimize data pipelines and ETL processes to handle large volumes of structured and unstructured data.
  • Ensure data integrity, security, and compliance with relevant regulations.
  • Create and maintain comprehensive data models, schemas, and documentation.
  • Evaluate and integrate new data technologies and tools to enhance our data infrastructure.
  • Provide technical leadership and mentorship to data engineers and analysts.
  • Stay current with industry trends and best practices in data architecture and AI.

Must-Have Qualifications

  • Bachelor\'s degree in computer science, Information Systems, or a related field.
  • Proven experience as a Data Architect, Senior Data Engineer, or in a similar data-focused role.
  • Minimum 8 years experience as a Data Architect, Senior Data Engineer, or in a similar data-focused role
  • Strong knowledge of database management systems, both SQL (e.g., Azure SQL, PostgreSQL) and NoSQL (e.g., Cosmos DB, MongoDB).
  • Proficiency in data modeling, data warehousing, and ETL/ELT pipelines using tools such as Apache Airflow, or Azure Data Factory.
  • Experience with big data technologies such as Apache Spark, Databricks, or similar.
  • Familiarity with cloud data platforms, preferably Microsoft Azure
  • Strong understanding of data governance, data quality, and data security practices.
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Understanding of CI/CD pipelines and DevOps practices for data workflows.
  • Knowledge of data privacy regulations such as GDPR, CCPA, or similar compliance frameworks.

Nice-to-Have Qualifications

  • Experience with big data technologies such as Apache Spark, Databricks, or similar
  • Experience with AI and machine learning frameworks (e.g., TensorFlow, PyTorch, Azure ML).
  • Knowledge of data visualization tools (e.g., Power BI, Tableau, Looker) and how to support reporting layers.
  • Exposure to real-time data processing and streaming technologies (e.g., Kafka, Azure Event Hubs, Stream Analytics).
  • Hands-on experience with Python, PySpark, or similar scripting languages for data transformation.
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