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AWS Data Platform / Platform Engineering Lead with SRE

Ravh IT SolutionsIrvine, CA🇺🇸United StatesPosted 13 Aug 2026

Quick Overview

Salary
$70 - $72/hr
Work Type
On Site
Level
Mid Senior

Job Description

AWS Data Platform / Platform Engineering Lead
Location: Irvine, CA
Work Arrangement: Onsite – 5 Days/Week
Rate: $70–$72/hr on W2
Client: TCS / Capital Group
Job Summary
We are seeking a highly experienced AWS Data Platform / Platform Engineering Lead to design, build, automate, and support enterprise-scale cloud data platforms and DevOps infrastructure.
The ideal candidate will have deep hands-on experience with AWS, Data Platform Engineering, Platform Engineering, Jenkins, CI/CD, Terraform, SRE, Infrastructure as Code (IaC), GitHub, SonarQube, ROC/D, and cloud-based DevOps.
This role will be responsible for building scalable and secure AWS data-platform infrastructure, developing automated CI/CD pipelines, implementing infrastructure automation, establishing code-quality controls, and improving platform reliability and operational excellence.
The candidate should be comfortable working across cloud infrastructure, data platforms, DevOps automation, CI/CD pipelines, infrastructure provisioning, deployment automation, and platform operations.
Key Responsibilities
AWS Cloud & Data Platform
  • Architect, build, and manage enterprise AWS data platforms supporting data engineering, analytics, reporting, and business-critical workloads.
  • Design scalable and highly available cloud-native data platform architectures.
  • Build and manage AWS infrastructure supporting data ingestion, processing, storage, transformation, and analytics.
  • Work extensively with AWS services such as S3, Glue, Redshift, Athena, Lambda, EMR, EKS, EC2, IAM, VPC, CloudWatch, KMS, and Secrets Manager.
  • Develop secure and reusable cloud infrastructure patterns for data engineering and analytics teams.
  • Implement AWS security, IAM, networking, encryption, access control, and governance.
  • Support data-platform scalability, reliability, performance, availability, and cost optimization.
  • Implement monitoring, logging, alerting, and observability for AWS data-platform environments.
  • Collaborate with Data Engineering, Architecture, Security, Application, and Infrastructure teams.
Data Platform Engineering
  • Build and support modern enterprise data-platform infrastructure.
  • Support Data Lake / Data Lakehouse architectures and cloud-based data workloads.
  • Enable data ingestion, batch processing, streaming, transformation, and analytical workloads.
  • Support technologies such as Databricks, Spark/PySpark, dbt, Airflow, AWS Glue, and Redshift.
  • Develop standardized infrastructure and deployment patterns for data engineering teams.
  • Implement data-platform security, governance, monitoring, availability, and operational standards.
  • Troubleshoot infrastructure and platform issues impacting data pipelines and analytics workloads.
Jenkins / CI/CD
  • Design, develop, and maintain enterprise CI/CD workflows using Jenkins Pipelines.
  • Build automated pipelines for source control, build, testing, quality validation, infrastructure provisioning, deployment, and release management.
  • Install, configure, and maintain Jenkins plugins required for Git/GitHub repositories and enterprise CI/CD workflows.
  • Configure SCM Polling, Git Webhooks, automated triggers, and pipeline orchestration.
  • Develop reusable Jenkins pipeline frameworks and Shared Libraries.
  • Integrate Jenkins with GitHub, Terraform, SonarQube, AWS, and other DevOps tools.
  • Troubleshoot Jenkins pipeline failures, deployment issues, build failures, and integration problems.
SonarQube / Quality Gates
  • Integrate SonarQube into Jenkins CI/CD pipelines.
  • Configure and enforce SonarQube Quality Gates.
  • Automate code-quality and security validation within CI/CD workflows.
  • Ensure code and deployments meet defined enterprise quality standards.
  • Monitor and resolve quality-gate failures before application or platform deployment.
Terraform / Infrastructure as Code
  • Design and implement AWS infrastructure using Terraform.
  • Develop reusable and standardized Terraform modules.
  • Automate provisioning and configuration of AWS infrastructure and data-platform components.
  • Integrate Terraform with Jenkins CI/CD pipelines.
  • Implement automated Terraform plan, validation, approval, and deployment workflows.
  • Manage infrastructure changes through Git-based version control.
  • Establish enterprise standards for Infrastructure as Code, automation, security, and governance.
ROC/D & DevOps Automation
  • Implement and support ROC/D within enterprise DevOps and CI/CD workflows.
  • Integrate ROC/D with applicable source-control, pipeline, deployment, and infrastructure automation processes.
  • Support automated release, deployment, and operational workflows involving ROC/D.
  • Troubleshoot ROC/D-related deployment, pipeline, and platform issues.
  • Work with engineering teams to standardize and automate release and operational processes.
Platform Engineering
  • Establish enterprise Platform Engineering standards, automation frameworks, and reusable platform capabilities.
  • Build self-service infrastructure and deployment capabilities for engineering and data teams.
  • Standardize development, testing, and production deployment processes.
  • Promote automation, GitOps, CI/CD, IaC, observability, security, and platform reliability.
  • Reduce manual infrastructure and deployment activities through automation.
  • Establish operational readiness, monitoring, incident management, and reliability practices.
  • Continuously improve platform scalability, availability, security, and engineering productivity.
Required Skills
Mandatory Technical Skills
  • AWS Cloud – Deep hands-on experience
  • AWS Data Platform Engineering – Deep experience
  • Platform Engineering
  • Jenkins / Jenkins Pipelines
  • CI/CD
  • Terraform
  • Infrastructure as Code (IaC)
  • Git / GitHub
  • SonarQube / Quality Gates
  • Cloud DevOps
  • Infrastructure Automation
  • Monitoring & Observability
  • Python, Bash, or Shell scripting
AWS Skills
Strong hands-on experience with multiple AWS services:
S3 | AWS Glue | Redshift | Athena | Lambda | EMR | EKS | EC2 | IAM | VPC | CloudWatch | KMS | Secrets Manager
Candidate must understand how AWS services are integrated to create and operate enterprise data platforms.
Data Platform Skills
Strong understanding of:
  • Data Lake / Data Lakehouse
  • Enterprise Data Platforms
  • Data ingestion and integration
  • Batch and streaming data processing
  • Data pipelines
  • Data transformation
  • Data storage and analytics
  • Data platform security
  • Data governance
  • Data quality
  • Platform monitoring and observability
  • High availability and disaster recovery
  • Data-platform performance and scalability
Databricks, Spark/PySpark, dbt, Airflow, AWS Glue, and Redshift experience is highly preferred.
Preferred Skills
  • Databricks
  • Apache Spark / PySpark
  • dbt
  • Apache Airflow
  • AWS Glue
  • Amazon Redshift
  • Amazon EMR
  • Kubernetes / Amazon EKS
  • Docker
  • GitOps
  • Jenkins Shared Libraries
  • Terraform Enterprise / Terraform Cloud
  • Python
  • Bash/Shell scripting
  • Cloud security and governance
  • Observability and monitoring
  • Financial Services / Investment Management experience
Ideal Candidate Profile
The ideal candidate should be a hands-on Platform/Data Platform Engineer or Lead, not simply a traditional DevOps Engineer.
The candidate should demonstrate strong experience across:
AWS Cloud + Data Platform + Platform Engineering + Terraform/IaC + Jenkins CI/CD + GitHub + SonarQube + ROC/D + DevOps
They should be able to design the AWS data-platform infrastructure, automate it using Terraform, build Jenkins CI/CD pipelines, implement SonarQube quality gates, support ROC/D workflows, and operate the platform in an enterprise production environment.
 

Skills

Docker
Shell
AWS
Encryption
SonarQube
Airflow
Apache
Apache Spark
Bash
Databricks
Git
Jenkins
Kubernetes
Python
Redshift
Terraform
dbt

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