Responsibilities:
- Platform Engineering & Operations:
Own AWS infrastructure for DXP Data Platform (multi-AZ, multi-VPC setup).
- Administer Snowflake environments, including user roles, RBAC, performance optimization, warehouse lifecycle, and cost controls.
- Manage SageMaker environments (Studio, Canvas, Notebooks) for enabling multi-domain ML use cases.
- Operate DataPipes (EKS + Airflow) for ingestion orchestration, ensuring high availability and version-controlled configurations via IaC (CloudFormation/CDK).
- Maintain & enhance logging, monitoring, observability & DevOps automation via modern tools such as CloudWatch, Splunk, PagerDuty, Slack, ServiceNow, Snowflake observability features.
- Platform Prototyping & Enhancement:
- Design, prototype, and implement new platform features across AWS, Snowflake, and SageMaker to support innovation in data processing, analytics, and ML operations.
- Lead rollout and production hardening of new platform components (e.g., new Snowflake Cortex AI features, SageMaker pipelines, AWS-native services).
- Evaluate and integrate new services or capabilities aligned to StarHub’s data platform roadmap.
- Develop technical design standards and documentation for new features and automation processes.
- Automation & Continuous Improvement:
Implement Day 2 platform enhancements including auto-scaling, self-healing workflows, and CI/CD automation.
- Enhance EKS cluster performance, pipeline automation, and integration efficiency across cloud and on-prem data sources.
- Drive infrastructure-as-code (IaC) adoption for all environments and standardize rollout strategies (blue-green/canary).
- Governance, Security & Compliance:
Enforce enterprise security policies for IAM, VPC isolation, PrivateLink, and encryption (KMS, Secrets Manager).
- Coordinate vulnerability remediation (EKS upgrades, CVE patching, EC2 AMI refresh, Docker image hardening).
- Ensure infrastructure audit readiness in partnership with Information Security (ITSec) and Compliance teams.
- Operations & Cost Management:
Monitor and optimize Snowflake warehouse utilization, compute spend, and S3 data lifecycle management.
- Maintain tagging, dashboards, and cost visibility frameworks across AWS and Snowflake.
- Implement cost governance guardrails and usage quotas across platform components.
- Team & Vendor Leadership:
Lead a blended team of StarHub engineers and partner vendors responsible for platform sustainment and evolution.
- Manage augmented vendor teams, ensuring consistent delivery quality and knowledge transfer to internal engineers.
- Build in-house capability in platform engineering, IaC, and automation disciplines.
Team Scope/ Stakeholders:
- Scope: DXP Data Platform infrastructure (AWS, Snowflake, SageMaker, Datapipe) supporting C360, AI/ML, and analytics workloads enterprise-wide.
- Decision Rights: Platform design approval, selection of new AWS/Snowflake/SageMaker capabilities, DevOps tooling and IaC framework choices, and vendor performance oversight.
- Stakeholders: Platform Engineering, Data Engineering, Data Science, Architecture & Governance, Information Security, and Infrastructure teams.
- Resources: Hybrid team of ~2-4 engineers (StarHub and partner resources) managing infrastructure, platform automation, enhancements, and operations.
Minimum Profile/ Track Record:
- 8-10 years of experience in cloud and platform engineering, with extensive experience on AWS-based data platforms.
- Proven leadership of cross-functional engineering teams managing production-grade, multi-environment platforms.
AWS Services: VPC, EC2, S3, RDS, Lambda, KMS, CloudFormation/CDK, Transfer Family, CloudWatch, CloudTrail.
Snowflake: administration, RBAC, warehouse optimization, DevOps automation, Cortex AI, and Streamlit integration.
EKS / Airflow / Airbyte (Datapipe): container orchestration, CI/CD pipelines, and deployment automation.
SageMaker: multi-domain setup, pipeline management, Studio/Canvas lifecycle, and MLOps enablement.
Monitoring & Observability: CloudWatch, Splunk, Snowflake Account Usage, cost dashboards, PagerDuty, Slack, ServiceNow.
- Demonstrated success in prototyping, implementing, and scaling new cloud and data platform features into production.
- Experience managing Day 2 operations, incident response, and SRE-driven performance stabilization.
- Familiarity with machine learning integration and model lifecycle management.
- Experience enforcing ITSec and compliance standards (IAM, KMS, PDPA/GDPR).
- Proven success in transitioning platform operations from vendor-managed to in-house ownership.