Backend & AI/ML Engineer
About The Position
NTT DATA is seeking a Backend & AI/ML Engineer to join their team. This role involves developing and supporting cloud-native data engineering solutions on Google Cloud Platform, building and maintaining data ingestion and processing pipelines using Databricks, and designing, deploying, and supporting GCP infrastructure using Terraform. The engineer will also develop and maintain CI/CD pipelines using GitOps methodologies, manage repositories and build artifacts using Azure DevOps and JFrog Artifactory, and support containerized applications running on GKE and Cloud Run. Additionally, the role includes developing integrations using Pub/Sub, Kafka, and REST APIs, working with GCP data services, monitoring and troubleshooting cloud infrastructure, implementing security best practices, and collaborating with cross-functional teams.
Requirements
- 5+ years of experience in DevOps, Cloud Engineering, or Data Engineering.
- 5+ years experience with Google Cloud Platform services including GKE, Cloud Run, BigQuery, AlloyDB, Cloud Storage, and serverless technologies.
- 5+ years experience with Databricks and data ingestion pipelines.
- 5+ years experience implementing CI/CD pipelines using GitOps and Azure DevOps.
- 5+ years experience with JFrog Artifactory.
- 5+ years experience implementing Infrastructure as Code using Terraform.
- 5+ years experience with Pub/Sub, Kafka, and API development.
Nice To Haves
- Understanding of GCP IAM, encryption, and cloud security best practices.
- Strong troubleshooting, analytical, and communication skills.
Responsibilities
- Develop and support cloud-native data engineering solutions on Google Cloud Platform.
- Build and maintain data ingestion and processing pipelines using Databricks.
- Design, deploy, and support GCP infrastructure using Terraform.
- Develop and maintain CI/CD pipelines using GitOps methodologies.
- Manage repositories and build artifacts using Azure DevOps and JFrog Artifactory.
- Support containerized applications running on GKE and Cloud Run.
- Develop integrations using Pub/Sub, Kafka, and REST APIs.
- Work with GCP data services including BigQuery, AlloyDB, Cloud Storage, and Spanner.
- Monitor, troubleshoot, and optimize cloud infrastructure and deployment pipelines.
- Implement IAM, encryption, and cloud security best practices.
- Collaborate with cross-functional teams to deliver scalable cloud solutions.
Benefits
- medical, dental, and vision insurance with an employer contribution
- flexible spending or health savings account
- life and AD&D insurance
- short and long term disability coverage
- paid time off
- employee assistance
- participation in a 401k program with company match
- additional voluntary or legally-required benefits
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
