Data & AI Architect

Position: Data & AI Architect 

Location: Vietnam - working remote/ hybrid

Job Type: Full-Time 

Work timings: Singapore Time zone 

Role Summary: 

We are looking for an experienced Data and AI Architect to lead the data platform modernization and AI implementation programs covering discovery, assessment, design and migration strategy for transitioning an On-Premises Data  Warehouse platform to a target Modernized On-Premises/Hybrid/Cloud Data Warehouse or Data Lakehouse platform.  Additionally, the role will also cover AI use case detailing and implementation using Cloud data and AI platforms. This role will be responsible for assessing the current environment, proposing a viable migration strategy with high-level architecture blueprints and designing of a target Data Lakehouse solution with AI capability overlay. The individual should be capable of evaluating technological options and providing cost-benefit analyses. This individual should also have sufficient knowledge of the data ecosystem and AI/ML concepts covering data engineering, data governance, AI model implementation, tune the AI/ML models, training, and visualization. The ideal candidate should have over 15+ years of experience in IT, with a majority of specialization in data and AI architecture design, solutioning, sizing and migration for on-premises and cloud-based solutions. 

Key Responsibilities: 

• Discovery & Assessment: 

o Conduct a thorough evaluation and assessment of our customer's current data warehouse platform to identify key pain points, challenges, business use cases, and opportunities for improvement.  

o Assess SQLs, ETLs, cubes, and other entities, integrations, consumers, data models and structures that need migration and transformation to move to new lakehouse. 

o Assess use case requirements, data readiness for AI implementation. Identify if it is Gen AI or AI/ML  requirement. Identify integration requirements and feasibility. 

o Understand customer requirements to adopt and implement the target state. 

o Identify security, governance and non-functional requirements. 

o Identify data migration requirements and risks, if any. 

• Design Architecture 

o Design Architecture for Data lakehouse on platform chosen for implementation. 

o Design AI blueprint architecture with integrations, security and governance requirements. o Define design decisions, dependencies and policies to be implemented. 

o Define environment sizing, integrations and non-functional design decisions. 

o Design DevOps integrated with the overall data platform and AI solution covering tools, configuration,  sizing and setup. 

o Design code repository and knowledge base structure to be adopted for delivery. 

o Lead design walkthrough and seek customer sign-off. 

o Review the low-level design and ensure implementation is aligned to design.

o Present to customer on solution and technical detailing. 

• Design Migration Strategy and Solution: 

o Design a comprehensive migration strategy that outlines the approach, mapping, data model, cutover strategy, timeline, and potential risks associated with the transition to a target data warehouse or Data  Lakes or to new AI model/solution. 

• Implementation 

o Govern the implementation through configuration, design adoption, testing and integration. 

o Develop and configure the ETLs, transformation logic, and integrations 

o Unit testing and support UAT 

o Cutover strategy implementation and ensuring smooth cutover 

o Post-production support 

• Technology Evaluation: 

o Research and evaluate various data and AI platform options, including on-premises, hybrid, and cloud-only solutions, to recommend the most suitable technology alignment with customers business objectives. 

o The recommendation of technology should be based on performing cost-benefit analyses and recommending the most viable technology stack with rationale. 

• Data Strategy: 

o Develop strategies for data acquisition, integration, transformation, pipeline creation, and data mart creation. 

o Develop a data strategy that defines the organization's data assets, data quality standards, and data usage policies. 

• Governance & Security: 

o Design a robust data governance and security framework to ensure data integrity, confidentiality, and compliance with relevant regulations. 

• Stakeholder Communication: 

o Collaborate with stakeholders to understand requirements and provide updates. 

o Ensure alignment with business objectives and technical needs. 

• Project Methodology: 

o Should have an understanding of project delivery methodologies such as Agile and DevOps to propose an implementation timeline. 

Must Have Skills and Knowledge:

• Experience: 15+ years in Data analytics, Data Lake and Data warehouse, Visualization domains and AI/ML, the majority of which is in designing and implementing production-grade Data engineering, analytics and AI/ML solutions.
• Domain Knowledge: Should have knowledge in at least 2 domains of expertise from Banking/ Insurance/ Fintech/ Manufacturing/ Logistics/ Telecom/ Media 
• Architecture Blueprint: As Architect, delivered at least 4 programs leading the design and implementation of data warehouse, data lake solutions and AI/ML solutions, with a deep understanding of data modeling for  OLAP applications, ETL processes, analytics and AI applications. Ability to design high-level architecture blueprints for data platforms and applied AI. 
• Migration Expertise: As Architect, led at least 2 programs for Data Warehouse migration or modernization.
• End-to-End Data  Processing: Good understanding of data domain concepts like data ingestion, data governance, data catalog,  data classification, data engineering, data analytics and data visualization
• Data Science and  Analytics: Good understanding of AI and ML and its integration with data platforms. 
• Platform Skills: Must have platform design and implementation experience in:

1. (Microsoft FABRIC, ADF and Power BI) 

2. Snowflake (2 years of production)

3. AWS Bedrock or Claude or similar AI model implementation 

4. Azure AI foundry 

• Technical Skills: AWS Cloud, Azure Cloud, Fusion, Fivetran, Airbyte, DBT, Airflow, Python, Pyspark, SQL 
• Governance &  Security: Experience in developing and implementing data governance frameworks, including data quality standards, metadata management, and data security measures for a data warehouse application. 
• Problem-Solving: Excellent problem-solving skills to identify and address challenges related to data migration and cloud adoption. 
• Communication  Skills: Strong verbal and written communication skills. 
• Certifications: Professional Architect certifications from at least one of the leading cloud providers (Azure, AWS,  Snowflake)

Good to Have Skills and Knowledge:

• DWH Technologies: Familiarity with Programing technologies like Python, Java, etc. Big Data Technologies like  Hadoop, Spark, or Kafka. Experience working with Relational and Non-Relational Database,  Columnar Database, NoSQL Database, Graph Database, etc. 
• On-prem and Cloud  Data Platforms: Experience with Databricks or AWS would be a plus, as would be good working knowledge of  on-prem data platforms 

Benefits & Perks at Cloud Kinetics

1. Healthcare & Insurance

● Social insurance, health insurance provided in accordance with Vietnamese labor regulations.

● Comprehensive private health insurance coverage for employees spouses and children.

2. Flexible Working Model

● Hybrid or Remote working arrangement with flexibility based on business and project requirements.

● A results-oriented work environment with non-fixed timekeeping, emphasizing ownership, performance, and outcomes.

3. Learning & Career Development

● Structured Learning & Development programs support continuous professional growth.

● Company sponsorship for employees pursuing international professional certifications aligned with their career development plans.

● Complimentary Udemy Business accounts for every employee to support continuous learning and upskilling.

4. Working Equipment: Company-provided equipment ensures employees have the tools they need to perform effectively.

5. Attractive OKR / Performance Bonus based on individual performance and overall company business results.

6. Recognition & Employee Engagement

● Multiple employee recognition programs celebrating outstanding contributions throughout the year.

● A vibrant company culture with regular engagement activities, including:

○ Company Trip

○ Year-End Party

○ Happy Hour

○ Team Building

○ Other internal events and employee engagement programs

Interested Send your resume to [Confidential Information] and we're ready to talk to you!