Introduction
As an AWS Data Engineer specializing in cloud-based data and AI-enabled data processing platforms, you will design, develop, and implement data engineering solutions using AWS services, with a focus on unstructured data processing, data classification, document extraction, natural language processing, and image analysis.
Your role and responsibilities
As an AWS Data Engineer specializing in cloud-based data and AI-enabled data processing platforms, you will design, develop, and implement data engineering solutions using AWS services, with a focus on unstructured data processing, data classification, document extraction, natural language processing, and image analysis.
This role requires a strong foundation in AWS Data Engineering, hands-on experience with AWS-native services such as Amazon Comprehend, Amazon Macie, Amazon Textract, and Amazon Rekognition, as well as good knowledge of serverless development and cloud-native integration patterns. Experience with AWS Lambda, Python or Node.js, and DevOps practices will be considered an advantage.
Your primary responsibilities will include:
• Design and Develop AWS Data Solutions: Design, build, and maintain scalable data pipelines and cloud-native data processing solutions using AWS services.
• Work with AWS AI and Data Services: Develop solutions using Amazon Comprehend for natural language processing, Amazon Macie for sensitive data discovery and classification, Amazon Textract for document and text extraction, and Amazon Rekognition for image and video analysis.
• Process Structured and Unstructured Data: Build data flows capable of ingesting, transforming, enriching, and analyzing structured, semi-structured, and unstructured data from multiple sources.
• Develop Serverless Components: Implement serverless processing logic using AWS Lambda, with Python or Node.js, to automate data processing, integration, and orchestration activities.
• Ensure Security and Data Governance: Apply AWS security best practices, including IAM, encryption, access control, monitoring, and sensitive data protection, especially when working with confidential or personal data.
• Optimize Data Pipelines: Improve the performance, scalability, reliability, and cost-efficiency of AWS-based data processing workflows.
• Collaborate on Solution Delivery: Work closely with architects, business analysts, application teams, security teams, and other stakeholders to deliver solutions aligned with business requirements.
• Support DevOps Practices: Contribute to deployment automation, CI/CD pipelines, infrastructure as code, environment management, monitoring, and operational support where required.
• Lead or Support Technical Delivery: Depending on seniority level, either independently deliver assigned components or take ownership of complex technical workstreams, providing guidance to other engineers when needed.
Required technical and professional expertise
• Strong experience in AWS Data Engineering.
• Hands-on experience with AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Athena, IAM, CloudWatch, and related AWS components.
• Practical knowledge of Amazon Comprehend, Amazon Macie, Amazon Textract, and Amazon Rekognition.
• Experience working with data ingestion, transformation, enrichment, and processing pipelines.
• Good understanding of cloud security, data privacy, and governance principles.
• Experience with Python and/or Node.js for automation, data processing, or serverless development.
• Ability to troubleshoot, optimize, and support cloud-based data solutions.
Preferred technical and professional experience
DevOps know-how, including CI/CD, infrastructure as code, Git-based workflows, and automated deployments.
• Experience with Terraform, AWS CloudFormation, GitHub Actions, Jenkins, or similar tools.
• Experience with event-driven architectures using services such as Amazon EventBridge, Amazon SQS, Amazon SNS, or Amazon Kinesis.
• Knowledge of GDPR, sensitive data classification, and enterprise data protection requirements.
• Experience integrating AWS AI/ML services into enterprise applications or data platforms.
IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.