Data Engineer, Forward Deployed Engineer

Overview In this role you design, deploy and optimize high-performance data infrastructure to fuel AI and autonomous workflows at client sites. You collaborate with architects, engineers and stakeholders in rapid prototyping to deliver production-ready systems that generate immediate business value. You join a modern triad of engineering, design and strategy in Kyndryl’s Lab, tackling real-world enterprise data challenges at scale. Compensation / Benefitsdiscretionary annual bonusmedical and dental coveragedisability benefitsretirement benefitspaid leave and PTOlearning and certification programs (Microsoft, Google, Amazon, Skillsoft) ResponsibilitiesDesign, optimize and maintain scalable ETL/ELT pipelines for batch and real-time processingArchitect distributed data systems across hybrid and cloud-native environments for performance and cost efficiencyTroubleshoot complex performance bottlenecks across diverse data storesDeploy and manage vector databases and semantic layers for high-context AI search and RAGBuild robust APIs for autonomous systems to access distributed datasetsConfigure feature stores to support active ML pipelines and real-time inferenceImplement data quality, observability and lineage tracking to ensure data fidelity and governanceCapture deployment insights and share learnings to accelerate future client implementationsBalance rapid prototyping with long-term platform stability to reduce technical debt Key requirementsStrong production-grade Python and advanced SQLETL/ELT pipelines with Airflow, dbt and KafkaCloud-native deployment on AWS, Azure or GCPExperience with vector databases (Pinecone, Milvus, Chroma, Weaviate) and vector indexingData quality, lineage and observability tools (Great Expectations, DataHub)Cloud certifications or willingness to obtain themBachelor’s degree in relevant field or equivalent professional experiencecustomer-focusedgrowth mindsetcollaboration across global teamsPythonSQL optimizationAirflow