Senior AWS Cloud Engineer (Data and AI)

webpuppies digital Singapore
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AI Summary

Looking for Senior AWS Cloud Engineers who live and breathe data. Responsible for designing and building end-to-end data platforms on AWS, architecting and deploying ML/AI solutions using Amazon SageMaker, and implementing data governance frameworks using AWS Lake Formation.

Key Highlights
Design and build end-to-end data platforms on AWS
Architect and deploy ML/AI solutions using SageMaker
Implement data governance frameworks using AWS Lake Formation
Key Responsibilities
Design and build end-to-end data platforms on AWS
Architect and deploy ML/AI solutions using Amazon SageMaker
Implement data governance frameworks using AWS Lake Formation
Lead technical design discussions
Mentor junior engineers
Technical Skills Required
AWS Glue Amazon QuickSight Amazon SageMaker AWS Lake Formation IAM Infrastructure as Code (CDK or Terraform) CI/CD pipelines for data and analytics workloads
Benefits & Perks
Opportunity to work with a top global consulting firm
Competitive compensation
AWS certification sponsorship
Nice to Have
Hands-on SageMaker experience: Studio, Pipelines, Feature Store, Model Monitor
Experience with Amazon Bedrock or SageMaker JumpStart for GenAI use cases

Job Description


Company Description

Webpuppies Digital, established in 2000, specializes in delivering innovative digital transformation solutions to clients across 21 countries, including Singapore government agencies, global enterprises, and SMEs. With over 25 years of expertise, we function as a strategic digital partner, focusing on aligning business goals with digital strategies to produce impactful results. Our expertise includes AI consultancy, smart systems integration, web and mobile application development, digital transformation, cloud solutions, and cutting-edge technologies such as VR, AR, FinTech, and PropTech. Webpuppies supports clients from strategy development to execution and ensures continuous support for sustainable growth.


Job Description


We’re looking for Senior to Lead-level AWS Cloud Engineers who live and breathe data - people who’ve built real pipelines, shipped real dashboards, and deployed real ML models on AWS. Not just certified, but battle-tested.

 

We’re scaling our data and AI practice to support system integration engagements with one of our top-tier global consulting firms. If you’ve ever built a medallion architecture on Glue, rolled out QuickSight to hundreds of users, or operationalized a SageMaker model in production - we want to talk.

 

WHAT YOU’LL DO

 

• Design and build end-to-end data platforms on AWS - from ingestion (Glue, Kinesis, AppFlow) through transformation (Glue ETL, Spark) to analytics (QuickSight, Athena, Redshift)

• Architect and deploy ML/AI solutions using Amazon SageMaker - including feature engineering, model training, real-time/batch inference, and MLOps pipelines

• Implement data governance frameworks using AWS Lake Formation, Glue Data Catalog, and IAM - with a focus on column/row-level security and audit compliance

• Build embedded analytics solutions and multi-tenant BI platforms using Amazon QuickSight, including SPICE optimization, RLS/CLS, and API-driven dashboard management

• Work embedded within client and SI partner delivery teams - operating under their AWS accounts, governance frameworks, and delivery methodologies

• Lead technical design discussions, produce architecture decision records, and mentor junior engineers on the team

• Contribute to reusable accelerators: Glue job templates, QuickSight dashboard templates, SageMaker project templates, and IaC modules (CDK/Terraform)

 

WHAT WE’RE LOOKING FOR

Must-Have:

• 5+ years of hands-on AWS experience, with deep expertise in at least two of: AWS Glue, Amazon QuickSight, Amazon SageMaker

• Proven experience building production data pipelines using Glue ETL (PySpark/Python Shell), including job bookmarks, crawlers, and Data Quality rules

• Strong understanding of data lake and data warehouse architecture patterns (medallion/lakehouse, star schema, slowly changing dimensions)

• Experience with Infrastructure as Code (CDK or Terraform) and CI/CD pipelines for data and analytics workloads

• Ability to work autonomously within client environments and communicate technical concepts to non-technical stakeholders

• Based in Singapore with the right to work locally

 

Strong Plus:

• Hands-on SageMaker experience: Studio, Pipelines, Feature Store, Model Monitor, real-time endpoints

• Experience with Amazon Bedrock or SageMaker JumpStart for GenAI use cases (RAG, fine-tuning, prompt engineering)

• QuickSight embedded analytics, namespace multi-tenancy, and QuickSight Q configuration

• Familiarity with Singapore regulatory frameworks: MAS TRM, PDPA, GCC (Government Commercial Cloud)

• AWS certifications: Solutions Architect Professional, Data Engineer Associate, Machine Learning Specialty

• Prior experience working in system integration or consulting delivery environments

 

WHAT’S IN IT FOR YOU

 

• Opportunity to work alongside one of our top global consulting firms on high-impact data and AI projects for their enterprise clients

• Be part of a growing data & AI practice where your technical decisions shape the direction

• Exposure to cutting-edge AWS services including GenAI, real-time ML, and embedded analytics

• Competitive compensation with AWS certification sponsorship

• Singapore-based, on-site role with a collaborative engineering-first culture

 

If you’ve read this far and thought “I’ve actually built this stuff” - that’s exactly who we’re looking for. Apply or DM me directly.

 

#AWS #DataEngineering #CloudEngineering #SageMaker #QuickSight #AWSGlue #Hiring #Singapore #DataAnalytics #MLOps #GenAI


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