\\\\Introduction\\\\ A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to modernize their data and cloud landscapes, accelerating adoption of hybrid cloud and AI-ready architectures. Your ability to drive meaningful change for clients is supported by our ecosystem of strategic partners and our technology platforms across the IBM portfolio; including Software and Red Hat. Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in measurable impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience. \\\\Your role and responsibilities\\\\ We are looking for motivated and tech-passionate individuals to: Collaborate with technical and business teams to support the implementation of data platforms on AWS Participate in the development of ingestion pipelines and data workflows following modern lakehouse patterns Contribute to the development and maintenance of batch and streaming ingestion components for data-driven solutions Apply basic cloud best practices for security, identity, and resource management under guidance from more experienced engineers Assist in configuring AWS core and analytics services as part of end-to-end data workloads Document technical tasks, data requirements, and implementation details to support delivery teams and clients \\\\Required technical and professional expertise\\\\ Minimum 1-2 years of experience working with cloud or data-related technologies (academic/bootcamp/project experience included) Basic understanding of data architecture concepts and modern data platforms Familiarity with AWS services commonly used in data workloads (e.g., S3, IAM, Glue, Lambda, Athena, Redshift) Foundational knowledge of data ingestion and transformation concepts (batch and/or streaming) Exposure to programming/scripting (e.g., Python, SQL, Bash) for automation and data tasks Interest in learning infrastructure-as-code tools (Terraform, CloudFormation, CDK) and cloud automation practices Motivation to pursue AWS certifications relevant to cloud data engineering or analytics \\\\Preferred technical and professional experience\\\\ Agile mindset, willingness to learn, adapt to changing priorities, take initiative, and apply critical thinking One of the following: Exposure to data governance or metadata management concepts Familiarity with hybrid or enterprise data integration scenarios (e.g., SAP-AWS) Understanding of basic cloud observability concepts and cost-awareness Exposure to containerization or orchestration (Docker, ECS, EKS, Kubernetes) IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

The role requires a minimum of 1-2 years of experience with cloud or data-related technologies, which can include academic, bootcamp, or project experience. A basic understanding of data architecture concepts and modern data platforms is necessary. Familiarity with common AWS services for data workloads such as S3, IAM, Glue, Lambda, Athena, and Redshift is expected. Foundational knowledge of data ingestion and transformation concepts, including batch and/or streaming, is also required. Exposure to programming or scripting languages like Python, SQL, or Bash for automation and data tasks is needed. An interest in learning infrastructure-as-code tools and cloud automation practices is also a requirement.