Cloud Data DevSecOps
Omniscius Consulting
Our client is seeking an experienced Cloud Data DevSecOps Engineer to build, automate, secure, and operate AWS-based big data infrastructure. This remote position will support cloud data platforms using infrastructure-as-code, AWS big data services, DevSecOps practices, and automation to ensure environments are scalable, secure, compliant, reliable, and cost-effective.
The ideal candidate has hands-on AWS cloud engineering experience and is comfortable working across client stakeholders, security teams, data engineering teams, infrastructure teams, and delivery teams.
Responsibilities
- Build, maintain, and enhance AWS infrastructure-as-code using CloudFormation or similar technologies.
- Design, support, and operate AWS big data services and platforms, including S3, EMR, Glue, Redshift, Kinesis, Lambda, and related services.
- Apply DevSecOps practices across cloud and data environments, including CI/CD pipelines, security scanning, IAM least-privilege design, and compliance guardrails.
- Develop scripts and automation using Python, Java, or similar languages to support infrastructure, data pipelines, deployments, monitoring, and operational requirements.
- Monitor, secure, scale, and troubleshoot AWS-based big data platforms.
- Identify and resolve performance, reliability, security, scalability, and cost optimization issues.
- Work with client stakeholders and technical teams to translate requirements into secure and scalable cloud data platform solutions.
- Create and maintain technical documentation, implementation plans, operational runbooks, and architecture artifacts.
- Collaborate across security, infrastructure, data engineering, and delivery teams to support successful implementation and ongoing operations.
- Clearly communicate complex cloud, data, security, and DevSecOps concepts to technical and non-technical stakeholders.
Required Qualifications
- Bachelor's degree or higher from an accredited college or university in Information Systems, Computer Science, Engineering, Data Engineering, or a related field.
- 5+ years of experience in cloud engineering, DevOps, data platform engineering, infrastructure engineering, or a related technical role.
- Hands-on experience building, automating, securing, and operating AWS-based environments.
- Experience with AWS big data services such as S3, EMR, Glue, Redshift, Kinesis, Lambda, or similar technologies.
- Experience with infrastructure-as-code, preferably AWS CloudFormation or a comparable IaC platform.
- Experience applying DevSecOps practices, including CI/CD pipelines, security scanning, IAM least-privilege design, and secure cloud configuration.
- Scripting or automation experience using Python, Java, or a similar programming language.
- Experience monitoring, troubleshooting, securing, and optimizing AWS data platforms for scalability, reliability, performance, and cost.
- Strong written and verbal communication skills with the ability to explain technical concepts clearly to clients and stakeholders.
- Ability to work effectively across client, security, infrastructure, data engineering, and delivery teams.
- Self-motivated and proactive with the ability to work independently while contributing effectively in a collaborative environment.
- U.S. Citizenship is required.
- Must be willing and able to undergo a background investigation for a Public Trust clearance/suitability determination.
Preferred Qualifications
- Experience working in FedRAMP, Public Trust, federal government, or other regulated cloud environments.
- Experience supporting production AWS data platforms with a focus on performance, scalability, security, reliability, and cost optimization.
- Experience working directly with clients, stakeholders, and cross-functional technical teams.
- Ability to communicate complex cloud, data platform, security, compliance, and DevSecOps concepts to both technical and non-technical audiences.
- Experience developing technical documentation, architecture diagrams, implementation plans, operational procedures, and runbooks.
- Familiarity with compliance guardrails, data governance, IAM and security controls, cloud risk management, or secure-by-design cloud practices.
- Experience estimating, planning, and communicating technical implementation approaches, tradeoffs, risks, and timelines for cloud or data platform initiatives.
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