Data Platform & Integration Solution Lead

Responsible for designing, building, and managing an enterprise data platform that integrates real-time and batch data, shapes enterprise data models, and provides data and services through APIs and application serving layers to support operational, analytical, and digital business needs.

Key Responsibilities:

Data Platform Architecture:

• Design a scalable, secure, and resilient enterprise data platform architecture.
• Define data integration standards for real-time, near-real-time, and batch processing needs.
• Develop a data platform blueprint aligned with the company's technology roadmap and business needs.

Real-Time Data Integration

• Design and implement CDC-based data ingestion (Change Data Capture).
• Develop an event streaming architecture using Kafka and Flink.
• Ensure near-real-time data flows meet established SLAs, reliability, and data consistency.

Batch Data Integration

• Integrate batch data sources from BigQuery and other systems.
• Design an efficient and scalable ETL/ELT process.
• Optimize data processing performance and costs.

Enterprise Data Modeling

• Design conceptual, logical, and physical data models.
• Develop data marts, canonical models, and data products that can be used across various business domains.
• Ensure data governance, metadata, and data quality standards are implemented across all platforms.
• Data Serving & API Enablement
• Design and manage an API Gateway as a single entry point for data and service consumption.
• Develop a service layer using Cloud Run or other container platforms.
• Provide secure, documented, and easy-to-use APIs and data services for internal and external applications.
• Cloud Platform & Engineering
• Manage the implementation of cloud-native solutions based on Google Cloud Platform.
• Build CI/CD, monitoring, logging, and observability for all platform components.
• Ensure platform security, availability, scalability, and cost optimization.

Governance & Collaboration

• Collaborate with application teams, data engineering, analytics, and business stakeholders.
• Develop architectural standards, best practices, and technical documentation.
• Provide technical guidance to engineers and vendors involved in platform development.