This position is not eligible for employer-sponsored work authorization or visa sponsorship (including initial, transfer, or extension), and candidates must be authorized to work in the United States at the time of application and remain authorized for the duration of employment without the need for sponsorship.
Bachelor's or master's incomputer science, Information Systems, Data Engineering, or related field (or equivalent experience).
10+ yearsdesigning and delivering enterprise data solutions, includinghands-onwork with bothtraditional DBMSandcloud nativedata platforms.
5+ yearsbuilding on cloud platformswith production experience in several of:S3, Glue, Lake Formation, Redshift, Athena, EMR/Spark, Kinesis/MSK, Lambda, Step Functions, EventBridge, SageMaker.
Demonstrated expertise implementingdata propagation Lakehousepatterns and governanceat scale.
Proven track record supportingAI/MLworkloads (feature stores, model data pipelines) and deliveringRAGsolutions with vector search on AWS.
StrongSQLandPython; proficiency indata modeling-IFC (preferred),3NF, dimensional/star, data vault, etc.
DBMS:SQL Server,PostgreSQL(schema, indexing, query planning, replication/HA, partitioning, backup/restore).
Data Engineering:Spark/EMR,Glue(ETL/ELT & Studio),Airflow/Step Functionsorchestration,Parquet/Delta/Iceberg.
Streaming/CDC:MSK/Kinesis,DMS(change data capture),event drivenpatterns.
Security & Governance:IAM,KMS,Lake Formation,Secrets Manager, data masking/tokenization, RBAC/ABAC.
AI/LLM enablement:Amazon Bedrock(Knowledge Bases, Guardrails, Agents), embeddings, chunking, retrieval,prompt design,token optimization, evaluation loops.
Observability & FinOps: Cloud logs/metrics, lineage/quality SLAs,cost controls(storage/compute), workload rightsizing.
DevOps/MLOps/IaC:Git,CI/CDfor data pipelines;Terraform/CDK; environment promotion; artifact/versioning; blue/green or canary for data jobs.