Data Lakehouse Architect

re-zoo-me; Singapore; On-site; SGD 112,000 - 134,000; Full time

Job summary

re-zoo-me in Singapore seeks a senior Lakehouse architect to lead end-to-end platform design and delivery. You will shape data products, data marketplace, and knowledge layer while enabling agentic workloads to run within the lakehouse environment.

The role requires 10-15 years in data lakehouse implementations, with hands-on experience across Cloudera, Huawei, Google Cloud, AWS, Azure and Open table formats. Competitive compensation up to SGD 11,000 monthly, depending on experience.

Qualifications

• 10–15 years of experience implementing a Data Lakehouse, preferably in the FSI domain.
• Experience in large-scale Lakehouse implementations and performance tuning.
• Open Table Formats: Iceberg, Hudi, Delta Lake; object storage strategies.
• Experience in designing data products, data marketplace, APIs/pub-sub/marketplace.

Responsibilities

• Own end-to-end architecture of the lakehouse platform.
• Design and implement data products, data marketplace, knowledge layer, and agentic workloads.
• Ensure quality assurance of delivery per Bank-defined software delivery methodology and tools.
• Partner with other technology functions to deliver required technology solutions.
• Provide technical vision and create roadmaps for the lakehouse platform.
• Create target architecture for applications emphasizing platforms, reusability, scalability and security.
• Develop frameworks and features for rapid operationalisation of patterns like unstructured extraction, lambda patterns, retrieval-augmented data, agentic workloads.
• Draft data contracts, SLAs, data quality rules for data products.
• Install, integrate and review software components; participate in product/tool selection via RFP/POC.

Skills

Big Data Architecture

Data Lakehouse

Performance optimization

RAG & Embeddings

API / Data Marketplace design

Tools

Databricks

Snowflake

Cloudera

Huawei

Google Cloud

AWS

Azure

Iceberg

Hudi

Delta Lake

Job description

Salary: Up to SGD 11000 / month (Depending on overall skills and experience)

We need consultants who have implemented a large-scale Lakehouse on one of the following platforms (Cloudera, Huawei, Google (Borderless Lakehouse, BigQuery, Looker), AWS (Outpost, EMR), Azure (Synapse)) and worked with Open table formats to implement a medallion architecture, implemented data-as-a-service using APIs/pub-sub/marketplace etc.

Key Responsibilities:

• You will be responsible for the end-to-end architecture of the lakehouse platform.
• This includes the design and implementation of data products, data marketplace, knowledge layer and enabling agentic workloads to run out of the lakehouse platform.
• You will also be responsible for quality assurance of the team’s delivery in conformance with the Bank-defined software delivery methodology and tools.
• You will partner with other technology functions to help deliver required technology solutions.

• Other responsibilities include:
• Provide technical vision and create roadmaps for the lakehouse platform
• Create the target architecture for an application / set of applications with emphasis on platforms, reusability, scalability and security
• Create frameworks, technical features which helps in faster operationalisation of new patterns such as unstructured content extraction, lambda architecture deployment patterns, retrieval-augmented data patterns, agentic workloads etc
• Effectively partner with business users to design data contracts, SLA, data quality rules for data products
• Independently install, customise and integrate software packages and programs
• Participate in selection of product/tools via RFP/POC.
• Create technical documents (functional/non-functional specification, design specification, training manual) for the solutions. Review design specifications created by development team
• Performance engineering and tuning
• Execute continuous service improvement and process improvement plans

Skills :

• TEAM Architecture (Big Data)
• 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
• Multi modal Query Engines (Hive, Impala, Apache Kudu etc)
• 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