IntroductionA 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 platforms. 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 ResponsibilitiesWe are looking for motivated and tech-passionate individuals to:Lead the development and maintenance of data ingestion pipelines and data platform components on AWSImplement data lake architectures leveraging Amazon S3, AWS Glue, AWS Lake Formation and modern table formats (e.G., Iceberg)Operate batch, streaming, and change data capture (CDC) ingestion patterns using services such as Amazon DMS, Amazon Kinesis Data Streams and Kinesis Data FirehoseIntegrate data from SaaS platforms and enterprise systems (e.G., SAP Datasphere) using Amazon AppFlowDevelop and optimize ETL/ELT transformations in Python, PySpark and SQL across Bronze/Silver/Gold data layersManage data cataloging, schema evolution and permission models through AWS Glue Data Catalog and AWS Lake FormationCollaborate with architects and platform leads to troubleshoot complex issues, optimize performance and resource usage, and ensure secure data operationsDocument technical implementations, operational procedures and best practices to support delivery teams and stakeholdersPreferred EducationBachelor\ 's DegreeRequired Technical And Professional ExpertiseMinimum 3–5 years of experience in data engineering and/or cloud data workloadsStrong hands-on experience in AWS analytics services such as AWS Glue, AWS Lake Formation, and Amazon S3Experience building ingestion pipelines using Amazon DMS (full load + CDC)Familiarity with streaming ingestion using Amazon Kinesis Data Streams and Kinesis Data FirehoseProficiency in ETL/ELT development using Python, PySpark and SQLKnowledge of modern data lake and lakehouse patterns including Iceberg, partitioning strategies, and data lifecycle managementExperience implementing multi-layer data models (Bronze/Silver/Gold)Experience managing data cataloging and permission models via AWS Glue Data Catalog and Lake FormationExposure to cloud security, IAM and cost-awareness in data workloadsInterest in pursuing AWS certifications aligned to data engineering or analyticsPreferred Technical And Professional ExperienceAgile mindset – willingness to learn, adapt to changing priorities, take initiative, and apply critical thinkingOne Of The FollowingExperience integrating SaaS platforms or SAP systems via Amazon AppFlow or similar toolsFamiliarity with hybrid enterprise integration scenarios (e.G., SAP Datasphere)Experience with observability tooling for data platforms (logging, metrics, tracing)Exposure to containerization/orchestration (Docker, ECS, EKS, Kubernetes)#J-18808-Ljbffr