обновлено 7 дней 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 and Governance): Owning the data lifecycle and roadmap for ingestion, modeling, governance, quality, security, and analytics enablement with an accent on scalable platform architecture and privacy compliance. Focus on building reliable pipelines, enforcing data quality and access controls, enabling self-service analytics, and managing engineers, analysts, and vendors.
Location: On-site in Bandar Sunway, Selangor, Malaysia
Company
is hiring for its information technology department.
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, and business intelligence.
- Build and operate ingestion pipelines for product, marketing, finance, and third-party data sources.
- Establish engineering practices including CI/CD, testing, code review, version control, and service levels for critical datasets.
- Implement data governance, quality management, access controls, masking, anonymisation, retention, and privacy-by-design practices.
- Manage data engineers and analysts, coordinate vendors, and enable self-service analytics through governed models and documentation.
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 modelling, and workflow orchestration.
- Experience with dimensional modelling, ELT design, data quality frameworks, PII handling, access control, PDPA, and GDPR.
- Ability to translate business requirements into data models, KPIs, and analytics outputs.
- Strong ownership, execution discipline, stakeholder communication, and people management 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, including Feast, Vertex, or AWS SageMaker pipelines.
- Experience with ISO 27001, SOC 2 Type II, PCI DSS, data retention, ROPA, DPIA/PIA, tokenisation, 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 confidence and develop professionally.
- A diverse working environment with colleagues from varied skill sets and experiences.
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