AWS- Data Engineer

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

Job summary

Ambition is seeking a Data Engineer to design and implement an end-to-end AWS data lakehouse, covering ingestion, storage, and analytics layers in a cloud-first environment.

You will work with AWS services such as S3, Glue, Redshift, Lambda, Kinesis, and Step Functions, building scalable pipelines, enforcing data quality, governance, and cost optimisation.

Qualifications

• Experience in designing data Lake/Lakehouse architectures and data governance.
• Hands-on work with batch and streaming data processing patterns.
• Proficient in SQL and one scripting language (Python or Scala).
• Experience with AWS data services and data ingestion pipelines.

Responsibilities

• Design and architect end-to-end AWS Data Lake and Lakehouse layers.
• Develop and deploy data ingestion pipelines for multiple sources.
• Implement data security, governance, and metadata management.
• Monitor platforms, troubleshoot pipelines, and optimise costs.

Skills

SQL proficiency

Python or Scala

Data governance

Cloud infrastructure

Architectural design

Tools

Amazon S3

AWS Glue

Amazon Redshift

AWS Lambda

Amazon Kinesis

AWS Step Functions

Amazon EventBridge

AWS AppFlow

AWS Lake Formation

Job description

We are seeking a Data Engineer with below key requirements:

Key Responsibilities

Architecture& Design

• Design and architect the end-to-end AWS Data Lake and Lakehouse solution, including Landing Zone, Transformed Zone, and Curated/Consumption Zone layers
• Define and govern data architecture standards, patterns, and best practices across the platform
• Architect reusable data ingestion pipelines supporting REST APIs, JDBC databases, S3 file uploads, and SaaS connectors (e.g. Salesforce via AWS AppFlow)
• Design data storage strategies including hot, warm, and cold storage tiers, encryption, and data lifecycle policies

Development& Deployment

• Develop and deploy data ingestion pipelines using AWS Glue, Lambda, Step Functions, EventBridge, and API Gateway
• Build and maintain data transformation workflows (batch and stream processing) using AWS Glue and Amazon Redshift
• Implement orchestration, monitoring, logging, and notification frameworks for pipeline operations
• Develop and maintain the AWS Glue Data Catalogue, including schema evolution tracking and metadata tagging

Security& Governance

• Configure and enforce data security policies using AWS Lake Formation, IAM, and Secrets Manager
• Implement granular access controls at database, table, and column levels
• Ensure compliance with data classification, retention, and audit requirements
• Support data quality frameworks and observability monitoring

Maintenance& Operations

• Monitor platform health, performance, and pipeline reliability
• Troubleshoot and resolve data pipeline failures and data quality issues
• Maintain documentation for architecture decisions, pipeline configurations, and operational runbooks
• Continuously optimise platform performance and cost efficiency on AWS

Requirements: Essential

• Minimum 3 to 5 years of experience in data engineering, data architecture, or cloud infrastructure roles
• Hands‑on expertise with core AWS data services: Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, Amazon Kinesis, AWS Step Functions, Amazon Event Bridge, AWS App Flow, AWS Lake Formation
• Strong proficiency in SQL and at least one scripting language (Python or Scala)
• Experience designing and implementing Data Lake or Lakehouse architectures
• Solid understanding of data governance, data cataloguing, and metadata management
• Experience with batch and streaming data processing patterns
• AWS Certified Data Engineer - Associate or AWS Certified Solutions Architect certification (or equivalent)

Regrettingly, only shortlisted candidates will be notified.

Business Registration Number: 200611680D|Licence Number: 10C5117 |EA Registration Number: R21102013