AI Accelerated Integration Engineer

Mandatory skills:
1.Python
2.AWS Lambda
3.REST API's

Role Overview
· Build production-grade data pipelines using Python.
· Develop scalable AWS Lambda REST APIs using Python.
· Deliver high-impact software in hours instead of days using AI tools.

Daily Responsibilities
· Design, build, and optimize data ingestion and transformation pipelines using modern Python data frameworks.
· Develop, deploy, and maintain serverless REST APIs and event-driven architectures on AWS.
· Leverage AI development assistants to rapidly write clean code, generate comprehensive test suites, and produce technical documentation.
· Participate in a high-velocity development life cycle, shifting from traditional multi-day delivery timelines to shipping high-impact products in hours.
· Integrate serverless AWS services with core data platforms to ensure reliable message delivery and state management.

Requirements
· Experience: 3 to 6 years of software or data engineering background.
· Data Engineering & Frameworks: Expert-level Python skills with hands-on experience using data frameworks such as Pandas and PySpark for data manipulation and processing.
· Core Skills: Advanced Python programming, data handling, and enterprise integration concepts/patterns.
· AWS Services: Deep operational knowledge of AWS integration offerings, specifically Kinesis, Lambda, SQS, EventBridge (Events), and API Gateway.
· Databricks: Familiarity with the Databricks platform is a plus, but not mandatory.
· AI Tooling: Super savvy at utilizing AI tools to accelerate coding, testing, and documentation tasks.