Data Lakehouse Architect

Saksoft Pte Ltd; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

Saksoft Pte Ltd is seeking a Data Lakehouse Architect to lead the end-to-end lakehouse platform design and delivery. The role focuses on building scalable data products, a data marketplace, and a knowledge layer to support agentic workloads and real-time analytics.

The candidate will drive architecture roadmaps, select tools, and ensure secure, scalable deployments across cloud/hybrid environments while collaborating with business users and technology teams.

Qualifications

• 10+ years of experience implementing a Data Lakehouse, preferably in FSI domain.
• Experience designing and optimizing large-scale lakehouse architectures.
• Knowledge of Iceberg, Hudi, Delta Lake formats.
• Experience with object storage tiers and data federation (e.g., Trino, Denodo, Dremio).
• Experience building hybrid/cloud workloads and IaC deployments.

Responsibilities

• Own end-to-end architecture of the lakehouse platform, data products, and data marketplace.
• Define the knowledge layer and agentic workloads running on the lakehouse platform.
• Ensure quality assurance of delivery per organisational software methodology.
• Partner with tech functions to deliver required technology solutions.
• Develop roadmaps and target architectures emphasizing scalability and security.
• Create frameworks to operationalise patterns like unstructured content extraction and retrieval-augmented data.

Skills

Team

Big Data Architecture

Education

Bachelor's degree in Computer Science, Engineering, or equivalent

Tools

Databricks

Snowflake

Cloudera

Google Cloud

AWS

Azure

Job description

Experience: 10+ Years
Role: Data Lakehouse Architect

Key Skills:
TEAM Architecture(Big Data)

• -10-15years of experience of implementing a Data Lakehouse preferable in FSI domain (usingplatforms such as Databricks, Snowflake, Cloudera, Huawei, Alibaba, GoogleCloud, AWS, Azure),
• -Experience in large scale implementationsand performance optimizations in the Lakehouse using
• a. OpenTable Formats such as Iceberg, Hudi, Delta Lake,
• b. ObjectStorage including tiered storage (hot, warm, cold data) strategies
• c. DataFederation such as Trino, Denodo, Dremio
• d. Multimodal 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

Responsibilities

• - You will be responsible for the end-to-end architecture of the lakehouse platform.
• o 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:
• o Provide technical vision and create roadmaps for the lakehouse platform
• o Create the target architecture for an application / set of applications with emphasis on platforms, reusability, scalability and security
• o 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
• o Effectively partner with business users to design data contracts, SLA, data quality rules for data products
• o Independently install, customise and integrate software packages and programs
• o Participate in selection of product/tools via RFP/POC.
• o Create technical documents (functional/non-functional specification, design specification, training manual) for the solutions. Review design specifications created by development team
• o Performance engineering and tuning
• o Execute continuous service improvement and process improvement plans

Requirements

Education

• - Bachelor’s degree/University degree in Computer Science, Engineering, or equivalent experience

Certifications

At least, 2 to 3 technical certifications in any of the below technologies:

1. 1. Cloud/Lakehouse Certifications – (Azure, AWS, GCP cloud certifications)
2. 2. DAMA Certified Data Management Professional, Databricks Certified Data Architect
3. 3. Data modelling tools (Erwin)
4. 4. Language – SQL, Java, Python, Scala, Javascript, node.js
5. 5. Automation / scripting – CtrlM, Shell Scripting, Groovy
6. 6. Vector DB (Databricks Vector Search, Azure AI Search, Pinecone, ChromaDB, Weaviate, Snowflake Cortex)
7. 7. Graph DB (Neo4J, Janusgraph, Tigergraph, Microsoft Fabric + Cosmos DB, Amazon Neptune, Stardog)
8. 8. Agentic Orchestration/Harness and Agentic Flow Frameworks (LangGraph, OpenAI Agents SDK, Microsoft Agent Framework, LlamaIndex Workflows, Google ADK)
9. 9. NOSQL / In-memory DB (Azure Cosmos DB, Redis, Amazon DynamoDB, Firestore, Redis/Valkey)
10. 10. Event Streaming (Apache Kafka, Confluent, Event Hubs, Kinesis)
11. 11. Real-time processing (Flink, Spark Streaming, NiFi, Structured Streaming)

Additional Experience required for all teams to create an added advantage

1. 1. CI/CD software - Jenkins, JIRA, Code pipelines, Azure pipelines, GCP Cloud Build + Deploy
2. 2. Code Quality – SonarQube
3. 3. Artifact Repository – Jfrog, CodeArtefact, ECR, Azure Artifacts, GCP Artifact Registry
4. 4. Source Code Version Control Tool – Git, Bitbucket
5. 5. Infrastructure-as-code – Terraform, Cloudformation, ARM
6. 6. Deployment Tool kit -Jenkins
7. 7. Monitoring – CloudWatch, Azure Monitor, Cloud Monitoring
8. 8. Service or Incident Management (IcM) Tools - Remedy
9. 9. Scheduling Tool - Control-M, Airflow
10. 10. Defect Management Tool - JIRA
11. 11. Application Testing tool – QuerySurge