{"id":1246491,"url":"https://alion.io/job/starhub-lead-data-platform-engineer","title":"Lead Data Platform Engineer","company":{"id":49913,"name":"StarHub","domain":"starhub.com","url":"https://alion.io/company/starhub","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Petaling Jaya, Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":46000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":432},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Blue-Green Deployment","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Cortex","optional":false},{"name":"CVE","optional":false},{"name":"Docker","optional":false},{"name":"GDPR","optional":false},{"name":"IAM","optional":false},{"name":"Machine Learning","optional":false},{"name":"PagerDuty","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Self-Healing","optional":false},{"name":"ServiceNow","optional":false},{"name":"Slack","optional":false},{"name":"Snowflake","optional":false},{"name":"Splunk","optional":false},{"name":"Kubernetes","optional":true},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2026-09-25T17:22:53Z","employer_posted_date":null,"last_verified_at":"2026-09-25T17:22:53Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Role Mission:To lead and scale theData Platform Engineering and Operationsfunction within StarHubs Digital Experience Platform (DXP) Data organization. This role ensures the continuousreliability, scalability, and securityof StarHubs C360 cloud data platform built on AWS, Snowflake, SageMaker, andDatapipe. The incumbent drivesoperational excellence, automation, and engineering maturityacross the platform, while prototyping and rolling outnew platform capabilitiesthat enable agility, innovation, and performance for data and AI workloads across the enterprise.\n\nAccountabilities:\nOwn end-to-endinfrastructure and platform operationsof the DXP Data Platform across AWS, Snowflake, and SageMaker environments (DEV, SIT, PROD).\n\nLead thedesign, build, and automation of data platform engineering and DevOps practices, ensuring continuous improvement and zero-downtime operations.\n\nLead the prototyping, implementation, and rollout ofnew platform capabilities and servicesacross AWS, Snowflake, and SageMaker.\n\nImplement governance,security, and compliance standards & improvementsfor cloud infrastructure, data access, and network controls.\n\nDrive operational excellence throughmonitoring, alerting, cost optimization, and performance tuning.\n\nManage a hybrid teamof internal platform engineers and vendor-augmented resources supporting Day 2 operations and enhancements.\n\nPartnerwith Data Engineering, Architecture, Security, Infrastructure & Tooling teams to ensure aligned technical roadmaps, compliance readiness, and audit traceability.\n\nResponsibilities:\nPlatform Engineering & Operations:\n\nOwn AWS infrastructure for DXP Data Platform (multi-AZ, multi-VPC setup).\n\nAdminister Snowflake environments, including user roles, RBAC, performance optimization, warehouse lifecycle, and cost controls.\n\nManage SageMaker environments (Studio, Canvas, Notebooks) for enabling multi-domain ML use cases.\n\nOperateDataPipes(EKS + Airflow) for ingestion orchestration, ensuring high availability and version-controlled configurations viaIaC(CloudFormation/CDK).\n\nMaintain & enhance logging, monitoring, observability & DevOps automation via modern tools such as CloudWatch, Splunk, PagerDuty, Slack, ServiceNow, Snowflake observability features.\n\nPlatform Prototyping & Enhancement:\n\nDesign, prototype, and implement new platform features across AWS, Snowflake, and SageMaker to support innovation in data processing, analytics, and ML operations.\n\nLead rollout and production hardening of new platform components (e.g., new Snowflake Cortex AI features, SageMaker pipelines, AWS-native services).\n\nEvaluate and integrate new services or capabilities aligned to StarHubs data platform roadmap.\n\nDevelop technical design standards and documentation for new features and automation processes.\n\nAutomation & Continuous Improvement:\n\nImplement Day 2 platform enhancements including auto-scaling, self-healing workflows, and CI/CD automation.\n\nEnhance EKS cluster performance, pipeline automation, and integration efficiency across cloud and on-prem data sources.\n\nDrive infrastructure-as-code (IaC) adoption for all environments and standardize rollout strategies (blue-green/canary).\n\nGovernance, Security & Compliance:\n\nEnforce enterprise security policies for IAM, VPC isolation,PrivateLink, and encryption (KMS, Secrets Manager).\n\nCoordinate vulnerability remediation (EKS upgrades, CVE patching, EC2 AMI refresh, Docker image hardening).\n\nEnsure infrastructure audit readiness in partnership with Information Security (ITSec) and Compliance teams.\n\nOperations & Cost Management:\n\nMonitor andoptimizeSnowflake warehouseutilization, compute spend, and S3 data lifecycle management.\n\nMaintain tagging, dashboards, and cost visibility frameworks across AWS and Snowflake.\n\nImplement cost governance guardrails and usage quotas across platform components.\n\nTeam & Vendor Leadership:\n\nLead a blended team of StarHub engineers and partner vendors responsible for platform sustainment and evolution.\n\nManage augmented vendor teams, ensuring consistent delivery quality and knowledge transfer to internal engineers.\n\nBuild in-house capability in platform engineering, IaC, and automation disciplines.\n\nTeam Scope/ Stakeholders:\nScope: DXP Data Platform infrastructure (AWS, Snowflake, SageMaker,Datapipe) supporting C360, AI/ML, and analytics workloadsenterprise-wide.\n\nDecision Rights: Platform design approval, selection of new AWS/Snowflake/SageMaker capabilities, DevOps tooling andIaCframework choices, and vendor performance oversight.\n\nStakeholders: Platform Engineering, Data Engineering, Data Science, Architecture & Governance, Information Security, and Infrastructure teams.\n\nResources: Hybrid team of 2-4 engineers (StarHub and partner resources) managing infrastructure, platform automation, enhancements, and operations.\n\nMinimum Profile/ Track Record:\n8-10years of experience in cloud and platform engineering, with extensive experience on AWS-based data platforms.\n\nProven leadership of cross-functional engineering teams managing production-grade, multi-environment platforms.\n\nHands-onexpertisein:\n\nAWS Services: VPC, EC2, S3, RDS, Lambda, KMS, CloudFormation/CDK, Transfer Family, CloudWatch, CloudTrail.\n\nSnowflake: administration, RBAC, warehouse optimization, DevOps automation, Cortex AI, andStreamlitintegration.\n\nEKS / Airflow /Airbyte(Datapipe):container orchestration, CI/CD pipelines, and deployment automation.\n\nSageMaker: multi-domain setup, pipeline management, Studio/Canvas lifecycle, andMLOpsenablement.\n\nMonitoring & Observability: CloudWatch, Splunk, Snowflake Account Usage, cost dashboards, PagerDuty, Slack, ServiceNow.\n\nDemonstrated success in prototyping, implementing, and scaling new cloud and data platform features into production.\n\nExperience managing Day 2 operations, incident response, and SRE-driven performance stabilization.\n\nFamiliarity with machine learning integration and model lifecycle management.\n\nExperience enforcingITSecand compliance standards (IAM, KMS, PDPA/GDPR).\n\nProven success in transitioning platform operations from vendor-managed to in-house ownership.","description_format":"text","description_chars":6111,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Broadband"],"lifecycle":[{"event":"open","at":"2026-09-25T17:22:53Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":35,"reasons":["seen:3","velocity","win:early","comp:brand"],"computed_at":"2026-09-29T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/starhub-lead-data-platform-engineer","json_url":"https://alion.io/job/starhub-lead-data-platform-engineer.json","meta":{"generated_at":"2026-09-30T04:04:38Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2691,"day_limit":5000,"remaining_today":2309,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}