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
