We are looking for an AI-enabled AWS Data Engineer who combines strong cloud data engineering expertise with a passion for modern platform engineering and AI-driven software delivery.

You will play a key role in migrating enterprise data platforms from Azure to AWS while helping evolve the organisation's Data Platform 2.0 into a scalable, self-service, Data as a Product ecosystem.

By leveraging AI-assisted engineering practices, you will accelerate delivery, improve platform quality, and contribute to building a future-ready data foundation that supports analytics, machine learning, and enterprise AI initiatives.

Desired Experience :

- 710+ years of Data Engineering experience.

- Experience migrating enterprise data platforms across cloud providers.

- Experience working in cloud transformation programmes.

- Experience building reusable platform capabilities.

- Experience working in Agile delivery teams.

- Experience with enterprise-scale datasets.

- Proven track record in cloud transformation, migration planning, and legacy modernization.

- Experience in Information Modeling, Domain-Driven Design, API and Integration Architecture.

Key Responsibilities :

- Design and implement migration of enterprise data workloads from Azure to AWS.

- Analyse existing Azure-based data pipelines and translate them into AWS-native solutions.

- Support migration planning, execution, validation, reconciliation, and production cutover.

- Ensure minimal business disruption during migration activities.

- Build and maintain scalable AWS data pipelines using services like AWS Glue, S3, EMR, Athena, Redshift, Kinesis.

- Collaborate with architects to implement strategic platform capabilities rather than project-specific solutions.

- Use AI-assisted development tools (e.g., Amazon Q, ChatGPT, Claude) to improve engineering productivity while maintaining engineering quality.

- Build reusable AI-enabled engineering patterns and accelerators for data migration and platform development.

Skills :

- Deep knowledge of AWS data and analytics platforms (MSK/Kafka, EventBridge, Kinesis, S3, Glue, Lambda, ECS/EKS, OpenSearch, DynamoDB).

- Strong expertise in real-time data streaming and event-driven architectures (Kafka, Pub/Sub, Event Streaming).

- Experience with SQL, Apache Spark and PySpark.

- Experience with ETL/ELT and Batch/Stream processing.

- Strong analytical and problem-solving skills.

- Ability to work with architects and translate designs into working solutions.

- Ownership mindset.

- Continuous learning attitude.