Data Architect - Manila

apartmentReed Elsevier placeManila scheduleFull-time calendar_month 
We’re seeking a Data Architect to help design and implement a scalable, flexible data architecture that connects siloed systems and supports enterprise-wide analytics, reporting, and AI initiatives. This role blends high-level architectural thinking with hands-on engineering work, enabling clean, secure, and accessible data across divisions.

You’ll be instrumental in shaping the standards, systems, and practices that will support our evolving data needs

Responsibilities
  • Design and implement enterprise-wide data architecture frameworks that support cross-division data integration and usability.
  • Develop scalable data pipelines and workflows (ETL/ELT) to support analytics, reporting, and machine learning workloads.
  • Collaborate with stakeholders across business units to identify data requirements and consolidate sources.
  • Lead efforts in data modeling, documentation, and establishing common data definitions and practices.
  • Define and implement data governance, data quality, and security frameworks aligned with compliance requirements.
  • Evaluate and recommend modern data technologies to support ongoing evolution of data infrastructure.
  • Partner with data engineers, analysts, and scientists to ensure data availability and usability.
  • Contribute to team growth by mentoring junior team members and promoting best practices in data engineering and architecture.
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.
  • 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 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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