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Open nowPosted 12 days ago

Enterprise Data & Analytics Architect

MyCareersFuture94,028 open roles

Pay
SGD 10,000 – SGD 14,000 a Monthly
Where
Singapore
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Your applicationOpen nowEnterprise Data & Analytics ArchitectMyCareersFuture · Singapore

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The clock on this job

Early applications get read.

7.7% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 12 days ago

The posting

Key Responsibilities

  • Own the end-to-end Data & Analytics architecture and technical vision for the enterprise.
  • Define and drive the Data & Analytics strategy, roadmap, architecture principles, standards, and reference architectures.
  • Design and architect enterprise-scale Data Lakehouse and Data Platform solutions.
  • Lead architecture across Databricks, Snowflake, Cloudera, Azure, AWS, and GCP environments.
  • Define architecture patterns for Delta Lake, Apache Iceberg, Hudi, Object Storage, Data Federation, and distributed data processing.
  • Develop target-state architecture for enterprise data platforms, analytics platforms, Data Lakehouse, data warehouses, data products, and AI platforms.
  • Define scalable and reusable architecture patterns supporting business intelligence, reporting, advanced analytics, AI/ML, and GenAI.
  • Assess existing data and analytics capabilities and identify opportunities for modernization, optimization, simplification, and technology transformation.
  • Ensure Data & Analytics architecture aligns with enterprise technology, security, regulatory, risk, and governance requirements.
  • Architect solutions using Trino, Denodo, Dremio, Hive, Impala, and other distributed data technologies.
  • Define and establish an enterprise data product strategy.
  • Design reusable, discoverable, governed, and trusted data products for business and analytical consumption.
  • Support development of data marketplaces and self-service data platforms.
  • Enable data products to support BI, reporting, analytics, AI/ML, and operational use cases.
  • Define architecture for Business Intelligence, reporting, dashboards, self-service analytics, and enterprise reporting platforms.
  • Partner with business and analytics teams to understand KPIs, metrics, analytical requirements, and reporting needs.
  • Support development of descriptive, diagnostic, predictive, and advanced analytics capabilities.
  • Define scalable analytical data models and semantic layers for enterprise consumption.
  • Enable trusted and consistent enterprise KPIs, metrics, and analytical insights.
  • Promote self-service analytics while maintaining appropriate governance, security, and data quality.
  • Architect solutions for AI/ML, Generative AI, RAG, Vector Databases, Graph Databases, embeddings, and agentic AI workloads.
  • Design event-driven and streaming data architectures using Kafka, Flink, Spark Streaming, APIs, and messaging platforms.
  • Define modern engineering practices for Data & Analytics platforms using Terraform, Kubernetes/OpenShift, Git, Jenkins, CI/CD, and DevOps tools.
  • Partner with business leaders, product owners, data analysts, data scientists, engineering teams, technology architects, and vendors.
  • Translate business requirements into practical and scalable Data & Analytics architecture.
  • Review and approve solution designs, technical specifications, architecture decisions, and implementation approaches.
  • Provide technical leadership to distributed engineering and delivery teams.
  • Ensure projects follow enterprise architecture, security, governance, and engineering standards.
  • Drive technical discussions, architecture reviews, design workshops, and technology evaluations.

Required Experience & Qualifications

  • 10–15 years of experience in Data & Analytics, Data Architecture, Data Engineering, Analytics Architecture, or related disciplines.
  • Strong experience designing and implementing enterprise-scale Data & Analytics platforms.
  • Proven experience defining Data & Analytics strategy, architecture, roadmaps, and target-state architecture.
  • Strong hands-on experience with Data Lakehouse, Data Warehouse, Data Platform, BI, and Advanced Analytics environments.
  • Experience working in FSI/BFSI, banking, financial services, insurance, or other highly regulated environments is preferred.
  • Strong expertise in one or more of Databricks, Snowflake, Cloudera, Azure, AWS, and GCP.
  • Strong knowledge of Delta Lake, Apache Iceberg, Hudi, Object Storage, Data Federation, and distributed data platforms.
  • Experience with Trino, Denodo, Dremio, Hive, Impala, or similar data technologies.
  • Strong understanding of data modeling, data warehousing, dimensional modeling, semantic layers, metadata, lineage, and data governance.
  • Experience designing data products, data marketplaces, analytical platforms, and self-service analytics.
  • Strong understanding of BI, reporting, KPI management, analytical workloads, and advanced analytics.
  • Experience with Kafka, Flink, Spark, Spark Streaming, APIs, real-time data, and event-driven architectures.
  • Strong knowledge of RAG, Vector DB, Graph DB, embeddings, AI/ML, Generative AI, and agentic AI workloads.
  • Experience with Terraform, Kubernetes/OpenShift, Git, Jenkins, CI/CD, and DevOps practices.
  • Strong understanding of data security, privacy, access control, governance, data quality, and regulatory requirements.
  • Experience with performance engineering, scalability, high availability, resiliency, and cloud cost optimization.
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