обновлено 3 дня назад
Data Engineer Manager
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer Manager (Data Platforms/Governance): Owning the data lifecycle and platform roadmap across ingestion, modeling, governance, quality, security, and analytics enablement with an accent on scalable architecture, privacy compliance, and self-service data access. Focus on building reliable pipelines, implementing dimensional and semantic models, managing data quality and access controls, and leading engineers, analysts, and vendors.
Location: On-site in Bandar Sunway, Selangor, Malaysia
Company
is hiring for an information technology role focused on building and governing its data platform.
What you will do
- Define and execute the data strategy and roadmap, prioritising dashboards, master data management, event tracking, experimentation readiness, and AI/ML readiness.
- Own the data platform stack across ingestion, transformation, storage, orchestration, metadata, business intelligence, and semantic layers.
- Build and operate ingestion pipelines for product, marketing, finance, and third-party data sources.
- Establish engineering practices covering CI/CD, testing, code review, version control, service levels, performance, reliability, and cost efficiency.
- Implement governance, data quality, privacy, security, access control, masking, anonymisation, and compliance practices.
- Lead engineers and analysts, coordinate vendors, and enable KPI definition, certified datasets, reporting standards, and self-service analytics.
Requirements
- 6–10 years of experience in data engineering or analytics, including ownership of data platforms or major data initiatives.
- Strong SQL skills and proficiency in at least one scripting language, preferably Python.
- Hands-on experience with modern data platforms such as Snowflake or BigQuery, data modeling, and workflow orchestration tools.
- Practical experience with dimensional modeling, ELT design, data quality frameworks, PII handling, access control, and privacy requirements including PDPA and GDPR.
- Ability to translate business requirements into data models, KPIs, and analytics outputs, with strong ownership and stakeholder communication skills.
Nice to have
- Experience with event analytics, product analytics, A/B testing, reverse ETL, and semantic layers such as LookML.
- Exposure to ML feature stores and MLOps tools such as Feast or Vertex/AWS SageMaker pipelines.
- Experience with ISO 27001, SOC 2, PCI DSS, data retention, ROPA, DPIA/PIA, tokenization, cross-border transfer controls, vendor risk, DPAs, and audit readiness.
Culture & Benefits
- Additional annual leave credited yearly.
- Medical and insurance coverage.
- Optical and dental subsidies.
- Training, guidance, and opportunities to build skills and confidence.
- Diverse workplace with opportunities for collaboration and professional growth.
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