Data Engineer - AWS Platform

Job Description :

This is a senior Data Architect role responsible for designing and leading the modernization of an enterprise data platform.

You will define the data strategy, create the target AWS architecture, standardize enterprise data models, and guide the migration from legacy systems to a modern real-time event-driven platform.

Key Responsibilities :

- Assess the current data, integration, and event-driven architecture landscape.

- Define the enterprise data strategy, target architecture, and implementation roadmap.

- Align on the canonical information/data model with the information modelling team.

- Architect a scalable AWS-based real-time data platform leveraging event-driven principles.

- Design and implement a compatibility/translation layer that converts the new canonical model into legacy formats to support existing consumers during migration.

- Establish data governance, metadata management, data quality, security, and observability standards.

Required Skills & Experience:

- 7 to 10+ years in Enterprise Data Architecture, Data Strategy, and Data Platform Modernization.

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

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

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

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

- Strong stakeholder management and the ability to translate business requirements into scalable technical solutions.

AI Expectations:

You will actively leverage AI to accelerate the transformation journey by :

- Analyzing existing integrations, schemas, and data flows to identify optimization opportunities.

- Assisting in the creation of canonical data models, event catalogs, and data dictionaries.

- Generating schema mappings and compatibility-layer transformation logic.

- Accelerating architecture documentation, design artifacts, and technical specifications.

- Supporting code generation, test automation, migration impact analysis, and data quality monitoring using AI tools such as GitHub Copilot, Amazon Q, ChatGPT Enterprise, or equivalent.

Expected Deliverables :

- Enterprise Data Strategy and Target-State Architecture.

- AWS Data Platform Blueprint.

- Canonical Information Model and Event Framework.

- Legacy Compatibility & Consumer Migration Strategy.

- Data Governance Framework.

- Prioritized Implementation Roadmap (12-24 months).

- AI Enablement and Acceleration Plan.

(ref:hirist.tech)