In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
As a Data Engineer at IBM, you'll play a vital role in the development, design of application, provide regular support/guidance to project teams on complex coding, issue resolution and execution.
- Your primary responsibilities include:
- Lead the design and construction of new solutions using the latest technologies, always looking to add business value and meet user requirements.
- Strive for continuous improvements by testing the build solution and working under an agile framework.
- Discover and implement the latest technologies trends to maximize and build creative solutions
- Design and Develop Data Solutions, Design and implement efficient data processing pipelines using AWS services like AWS Glue, AWS Lambda, Amazon S3, and Amazon Redshift.
- Develop and manage ETL (Extract, Transform, Load) workflows to clean, transform, and load data into structured and unstructured storage systems.
- Build scalable data models and storage solutions in Amazon Redshift, DynamoDB, and other AWS services.
- Data Integration: Integrate data from multiple sources including relational databases, third-party APIs, and internal systems to create a unified data ecosystem.
- Work with data engineers to optimize data workflows and ensure data consistency, reliability, and performance. Automation and Optimization: Automate data pipeline processes to ensure efficiency
- Define, drive, and implement an architecture strategy and standards for end-to-end monitoring.
- Partner with the rest of the technology teams including application development, enterprise architecture, testing services, network engineering,
- Good to have detection and prevention tools for Company products and Platform and customer-facing
