Senior AWS Data Platform Architect & Leader

Our Clients

Philippines

On-site

PHP 2,000,000 - 4,200,000

Full time

10 days ago

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Job summary

Our Clients in Philippines seeks an AWS Lead to provide technical leadership in modern data platforms on AWS. Lead architecture, data ingestion, and analytics pipelines across batch, streaming, and near real-time workloads.

Drive security, governance, and cost optimization while mentoring delivery teams. The role requires 10–15+ years in data/analytics, 7–10+ years delivering enterprise AWS data platforms, and strong stakeholder engagement.

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or a related discipline.
10–15+ years of experience in data, analytics, business intelligence, cloud, or related technology domains.
7–10+ years of experience designing and delivering enterprise-scale AWS data platforms.
Proven experience defining modern data strategies and cloud-based data architectures.
Demonstrated experience providing technical leadership across complex data and analytics initiatives.
Strong experience working with business and technical stakeholders in enterprise environments.

Responsibilities

Lead the architecture and design of enterprise-scale modern data platforms using AWS.
Define scalable architectures covering data lakes, data warehouses, and lakehouse environments.
Establish reusable architecture patterns and technical standards for data ingestion, integration, modelling, governance, security, and access.
Provide technical direction to data engineers, developers, consultants, and other delivery teams.
Review solution designs and implementations to ensure alignment with architecture, security, scalability, performance, and cost requirements.
Provide technical guidance on AWS service selection and appropriate architecture patterns for different data workloads.
Lead the design and implementation of modern data platforms using AWS services such as S3, Glue, Redshift, Athena, Kinesis.
Oversee the development of data ingestion, transformation, integration, and analytics pipelines.
Support appropriate processing patterns across batch, streaming, and near real-time data workloads.
Enable reliable data consumption for analytics, business intelligence, reporting, and downstream applications.
Ensure data platform solutions are designed for scalability, reliability, maintainability, and operational readiness.