For more than 20 years, our global network of passionate technologists and pioneering craftspeople has delivered cutting-edge technology and game-changing consulting to companies on the brink of AI-driven digital transformation. Since 2001, we have grown into a full-service digital consulting company with 5500+ professionals working on a worldwide ambition. Driven by the desire to make a difference, we keep innovating. Fueling the growth of our company with our knowledge worker culture. When teaming up with Xebia, expect in-depth expertise based on an authentic, value-led, and high-quality way of working that inspires all we do. About the Role We’re looking for a highly capable AWS Data Engineer to join our growing Data & AI team. You’ll be designing and building robust, scalable data solutions leveraging the AWS cloud ecosystem—focusing on real-time streaming, event-driven architecture, and microservices. If you thrive in a collaborative environment, have a passion for automation and quality, and believe in clean, testable code, we want to hear from you. What You’ll Do Cloud-Native Data Engineering on AWS Design and implement data pipelines using AWS services like Lambda, Kinesis, EventBridge, and DynamoDB. Build scalable APIs and microservices using Python 3.6+, FastAPI, GraphQL, and Pydantic. Work with infrastructure-as-code using AWS CDK to provision cloud resources securely and reproducibly. Monitor and troubleshoot cloud-native data applications using CloudWatch and related observability tools. Engineering Practices & Collaboration Apply best practices of SDLC, including Test-Driven Development (TDD), Continuous Integration (CI), and Continuous Delivery (CD). Collaborate across teams using GitLab for version control, pipeline automation, and issue tracking. Participate in design reviews, peer code reviews, and mentor junior engineers. Document architecture decisions, API contracts, and operational procedures. Streaming, Eventing, and Real-Time Processing Develop and support real-time streaming solutions using AWS Kinesis and EventBridge. Implement and manage event-driven data flows and microservices patterns. Integrate streaming data with downstream analytics or storage systems (e.g., S3, What You Bring 5+ years of professional experience in Python (v3.6+), including familiarity with Pytes or similar frameworks. Deep understanding of core AWS services: Lambda, S3, DynamoDB, EventBridge Kinesis, CloudWatch, and CDK. Proven experience designing APIs/microservices with FastAPI, GraphQL, and Pydantic. Strong knowledge of GitLab workflows and CI/CD practices. Solid grasp of data engineering principles, SDLC, and test-driven development. Experience with real-time data and event-driven architecture. Availability to work thru EST timezone Nice to have: Knowledge of additional Python tools and libraries for data (e.g., Pandas, boto3) Experience with containerization (Docker) or serverless-first design patterns Exposure to schema evolution, data contracts, or metadata management Apply for this job * indicates a required field First Name * Last Name * Email * Phone * Resume/CV * Enter manually Accepted file types: pdf, doc, docx, txt, rtf LinkedIn Profile * Primary Skill Select... Degree in Information Systems, Computer Science, with 4 or more years of experience Deep understanding of AWS Cloud tools and technologies, including but not limited to CDKs, Lambda, DynamoDB, and S3 Python v3.9 or higher and Python frameworks, such as Pytest Experience in developing, writing and executing test cases, and deploying code Experience with data engineering, data modeling, real time streaming and/or eventing, and json parsing Experience in building micro services and APIs utilizing Pydantic and Graphql #J-18808-Ljbffr