About
DevOps/Platform Engineer (1 Position)
Experience Required:
5-7 years
Project:
Boeing BDS DADI Data Platform - Data Ingestion & ETL Duration:
April 1, 2026 - September 30, 2026 (6 months) Location:
Onsite (US-based) Eligibility:
All resources must be U.S. Citizens or Green Card holders
Role Summary: The DevOps/Platform Engineer ensures that all ingestion and ETL pipelines are deployed reliably through automated CI/CD processes, infrastructure is provisioned as code, and the platform operates efficiently with proper autoscaling and cost controls. This role bridges the gap between pipeline development and production-grade operations.
Key Responsibilities: Build and maintain CI/CD pipelines for automated testing, validation, and deployment of ingestion and ETL workloads across dev, staging, and production environments. Implement infrastructure-as-code (IaC) for all pipeline-related cloud resources using Terraform, CloudFormation, or CDK. Configure and manage secrets, credentials, and cross-account/VPC connectivity required for source system integration. Develop autoscaling patterns for ingestion compute resources to handle variable data volumes cost-effectively. Implement cost monitoring dashboards and provide ongoing optimization recommendations for ingestion compute spend. Collaborate with Boeing's platform, security, and network teams for approvals, quota increases, and connectivity provisioning. Ensure deployment processes support zero-downtime updates and rollback capabilities. Manage environment configurations, branching strategies, and release processes aligned with Boeing's CI/CD guidelines. Support the QA engineer with test environment provisioning and pipeline validation automation. Required Skills & Qualifications:
5-7 years of experience in DevOps, platform engineering, or site reliability engineering (SRE) with a focus on data platforms. Expert-level AWS experience: IAM, VPC, CloudFormation/CDK/Terraform, CodePipeline, CodeBuild, ECS/EKS, S3, KMS. Strong experience building CI/CD pipelines for data workloads (not just application deployments). Proficiency in infrastructure-as-code: Terraform (preferred) or CloudFormation/CDK. Experience with container orchestration (ECS, EKS) and serverless compute (Lambda, Glue). Hands-on knowledge of secrets management (AWS Secrets Manager, Parameter Store) and cross-account IAM patterns. Understanding of cost optimization levers for AWS data services (Glue, EMR, Kinesis, S3). Familiarity with monitoring tools: CloudWatch, Grafana, and alerting configuration. Scripting proficiency in Bash, Python, or similar. Experience working in regulated or security-conscious environments. Preferred Skills:
AWS certifications (Solutions Architect, DevOps Engineer). Experience with GitOps workflows (ArgoCD, Flux). Familiarity with FinOps practices and AWS cost management tooling. Prior experience supporting data lake or lakehouse infrastructure.
Languages
- English
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