Elias Delosreyes

Senior Data Engineer / Data Platform Engineer (ex-Amazon, Expedia) building AWS-native data platforms, ingestion frameworks, and distributed systems. 8+ years across platform reliability, orchestration, and performance—from SaaS/API ingestion to PB-scale warehouses and high-throughput streaming. Recent scale/impact: • Amazon Logistics: operated a global Redshift warehouse (10+ PB; 300T+ rows/day), workload management, tuning, and data lake integrations (Glue/Lake Formation/Spectrum/Athena). • Expedia: supported 1M+ Spark jobs/month across ~4,000 apps (Spark on EMR + Spark-on-Kubernetes/EKS); supported 100+ Airflow clusters on EKS; heavy incident/debug + performance work. • NBCUniversal: modernizing SSIS/PowerShell → Airflow (MWAA) + Glue; building S3/Iceberg lakehouse foundations; Terraform + GitHub Actions CI/CD. What I do: • Data platform engineering: ingestion frameworks, orchestration, Spark runtime/perf debugging (shuffle/skew, partitioning/file layout, executor sizing, configs). • Reliability & observability: SLAs/SLOs, metrics/logs/traces, runbooks, alerting/on-call hygiene (CloudWatch, Datadog/Splunk), automated retries/backoff. • Infra as Code & delivery: Terraform/CDK/CloudFormation, CI/CD (GitHub Actions/Jenkins), multi-account AWS, least-privilege IAM, STS role chaining. • Data modeling & query performance: dimensional/star schemas, Redshift tuning (DIST/SORT, vacuum/analyze, WLM/QMR), cost optimization. Core stack: Python, SQL, Spark (PySpark), Airflow (MWAA), AWS (S3, Redshift, Glue, EMR, Athena, Lake Formation, Kinesis, Lambda, IAM, STS), Kubernetes/EKS, Docker, Terraform, GitHub Actions, Jenkins, Git. Datastores: Redshift, PostgreSQL, MySQL, SQL Server, DynamoDB, MongoDB. Preferences: Open to fully remote senior IC roles in data engineering / data platform / data infrastructure / data reliability. Please include comp range when reaching out. Specialties/keywords: Senior Data Engineer, Data Platform Engineer, Data Infrastructure Engineer, Data Reliability Engineer, Platform Engineer, Cloud Data Engineer, Lakehouse, Apache Iceberg, Apache Spark, Airflow, MWAA, EMR, Kubernetes, AWS, Redshift, Glue, Terraform, CI/CD, IAM, STS, data pipelines, ETL/ELT, ELT, DataOps, GitOps, Kinesis, SQS, SNS, Lambda, observability, and performance tuning.