Data Lakehouse Architect opening in Singapore

R Systems; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

R Systems seeks an expert in Data Lakehouse architectures to lead large-scale implementations in FSI. You will optimize performance, design for hybrid and cloud environments, and implement data products using Iceberg, Delta Lake, and associated tools.

The role involves building scalable data platforms, integrating with APIs, and publishing real-time dashboards and marketplaces for downstream applications.

Qualifications

• 10-15 years in data lakehouse implementations, preferably in FSI.
• Experience with large-scale performance optimizations in Lakehouse environments.
• Knowledge of Iceberg, Hudi, Delta Lake and related formats.
• Experience with federation tools like Trino, Denodo, Dremio.
• Designs for hybrid/cloud workloads and private connectivity strategies.
• Experience building data products and publishing APIs or streams.

Skills

Data Lakehouse architecture

Databricks

Snowflake

Cloudera

Cloud platforms (GCP/AWS/Azure)

Iceberg

Hudi

Delta Lake

Trino

Denodo

Dremio

Kubernetes

OpenShift

Helm

Kustomize

Infrastructure-as-Code

APIs and data products

RAG/Embedding/Vector DB

Tools

Databricks

Snowflake

Cloudera

Iceberg

Hudi

Delta Lake

Trino

Denodo

Dremio

Kubernetes

OpenShift

Helm

Kustomize

Terraform/Infra-as-Code

Job description

• 10-15 years of experience of implementing a Data Lakehouse preferably in FSI domain (using platforms such as Databricks, Snowflake, Cloudera, Huawei, Alibaba, Google Cloud, AWS, Azure),
• Experience in large scale implementations and performance optimizations in the Lakehouse using
• Open Table Formats such as Iceberg, Hudi, Delta Lake,
• Object Storage including tiered storage (hot, warm, cold data) strategies
• Data Federation such as Trino, Denodo, Dremio
• Experience in designing MPP and Distributed Compute workloads across on-premise, hybrid and cloud environments
• Experience in serving agentic workloads using RAG, Embedding strategies, Vector DB, Graph DB, prompt engineering, context management etc
• Experience in designing optimal hybrid and cloud workloads using private dedicated connectivity (Direct Connect, Express Route etc), workload placement strategy, egress cost optimization, Infrastructure-as-Code,
• Experience in building foundation and business data products and serving them to downstream applications via API, pub-and-sub, generative BI, real-time dashboards, etc and publishing to a data marketplace
• Knowledge of migrating workloads out of MPP appliances such as Teradata, Greenplum, Netezza using bulk migration strategies, agentic accelerators is a plus
• Knowledge of containerization, deploying applications to Kubernetes, Openshift using Helm package manager, Kustomize etc is a plus

Expertise in integrating applications with Devops tools