Job Role- Data/ Platform Engineer
Location- Reston, VA
Duration- Full Time
Job Description
We are seeking a Data Platform Infrastructure Engineer with 6+ years of experience and strong AWS cloud skills and hands-on experience supporting modern data platforms such as AWS EMR, AWS Glue, and Databricks across development, test, and production environments.
This resource will be responsible for building, configuring, and maintaining secure, scalable, and production-ready data platform infrastructure. The role requires experience with AWS services, data processing platforms, infrastructure automation, CI/CD support, monitoring, resiliency, governance, and platform optimization.
Key Responsibilities
- Design, implement, and manage cloud-based data platform infrastructure across development, test, and production environments
- Work with AWS services such as IAM, VPC, S3, KMS, CloudWatch, Lambda, EMR, Glue, and related networking/security services
- Provision, configure, and support data processing platforms including EMR, Glue, and Databricks
- Implement secure networking, connectivity, encryption, and access controls
- Manage identity, role-based access, secrets, and platform security configurations
- Support data governance, cataloging, metadata management, and storage integration
- Automate infrastructure deployment and configuration using Terraform
- Support CI/CD processes for platform deployment and environment promotion in GitLab
- Establish monitoring, alerting, logging, and operational support processes
- Support resiliency, disaster recovery, backup, and recovery planning activities
- Define and enforce cost, performance, security, and usage guardrails for the platform
Required Experience
- Development Experience with Python and PySpark
- Experience managing Databricks platform infrastructure
- Experience with AWS services and developing solutions in the AWS cloud, including but not limited to:
- EC2, Lambda, S3, EFS, Glue, EMR, CloudWatch, IAM
- Experience with AI-assisted development tools and practices
Desired Experience
- Strong written and verbal communication skills.
- Self-driven individual with the ability to take initiative, demonstrate accountability, and assume responsibility.
- Ability to work independently with minimal guidance or supervision.
- Ability to learn quickly and master new technical and business areas.
ience supporting modern data platforms such as AWS EMR, AWS Glue, and Databricks across development, test, and production environments.
This resource will be responsible for building, configuring, and maintaining secure, scalable, and production-ready data platform infrastructure. The role requires experience with AWS services, data processing platforms, infrastructure automation, CI/CD support, monitoring, resiliency, governance, and platform optimization.
Key Responsibilities
- Design, implement, and manage cloud-based data platform infrastructure across development, test, and production environments
- Work with AWS services such as IAM, VPC, S3, KMS, CloudWatch, Lambda, EMR, Glue, and related networking/security services
- Provision, configure, and support data processing platforms including EMR, Glue, and Databricks
- Implement secure networking, connectivity, encryption, and access controls
- Manage identity, role-based access, secrets, and platform security configurations
- Support data governance, cataloging, metadata management, and storage integration
- Automate infrastructure deployment and configuration using Terraform
- Support CI/CD processes for platform deployment and environment promotion in GitLab
- Establish monitoring, alerting, logging, and operational support processes
- Support resiliency, disaster recovery, backup, and recovery planning activities
- Define and enforce cost, performance, security, and usage guardrails for the platform
Required Experience
- Development Experience with Python and PySpark
- Experience managing Databricks platform infrastructure
- Experience with AWS services and developing solutions in the AWS cloud, including but not limited to:
- EC2, Lambda, S3, EFS, Glue, EMR, CloudWatch, IAM
- Experience with AI-assisted development tools and practices
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