Aws data engineer

About the Job

We are seeking a skilled Data Engineer to architect, build, and optimise scalable data platforms on cloud infrastructure. The role involves close collaboration with cross-functional teams to deliver robust, secure, and high-performance data solutions that support analytics and business operations.

Core Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines, data lakes, and data warehouse solutions.
• Build and optimize data ingestion frameworks for batch and real-time processing.
• Develop and deploy containerised applications using Docker, Amazon ECR, and Amazon ECS.
• Design and implement RESTful APIs for system integrations using modern frameworks (e.g., Fast API).
• Implement Infrastructure as Code (Ia C) using Terraform and AWS Cloud Formation.
• Establish and maintain CI/CD pipelines for automated build, test, and deployment workflows.
• Ensure adherence to data security, governance, and compliance standards (e.g., encryption, access control).
• Monitor, troubleshoot, and optimise data workflows for performance and reliability.

Required Skills

• Strong proficiency in Python and SQL for data processing and transformation.
• Hands-on experience with Fast API for API development.
• Experience with distributed data processing frameworks such as Py Spark.
• Solid experience with AWS services, including:

Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena

AWS Lambda, AWS DMS, API Gateway

• Experience with containerization and orchestration (Docker, ECS).
• Strong understanding of cloud-native architecture and best practices.
• Excellent problem-solving, communication, and collaboration skills.

Nice to have

• Exposure to Generative AI and Agentic AI concepts.
• Hands-on experience with LLM frameworks such as Lang Chain, Llama Index, or Crew AI.
• Experience working with LLMs and NLP models (e.g., GPT, BERT, LLa MA, Mistral, Gemini).
• Familiarity with LLM-as-a-Service platforms such as AWS Bedrock or Hugging Face.
• Basic understanding of ML model deployment and lifecycle management.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• 3–5 years of hands-on experience in Data Engineering and AWS cloud environments.