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# Cloud Data Platform Engineer/Owner

- **Company:** Snowflake Inc.
- **Location:** Boston, MA, United States (Remote available)
- **Contract:** Temporary to permanent
- **Skills:** Query Performance, Microsoft Access, Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Cloud Computing, Computer Networks, Databases, Continuous Integration, Information Engineering, Data Infrastructure, Data Integrity, Data Masking, Data Security, Data Sharing, Data Warehousing, DevOps, Github, Identity and Access Management, Python (Programming Language), Performance Tuning, Role-Based Access Control, DataOps, Software Deployment, Workflow Management Systems, Enterprise Data Management, Data Logging, Scripting, Data Ingestion, Snowflake, Data Build Tool (dbt), Boto3, Infrastructure as Code (IaC), Git, Containerization, Gitlab-ci, Deployment Automation, Data Management, Cloud Integration, Terraform, Software Version Control, Docker, User Administration, Jenkins
- **Published:** October 2, 2026
- **Apply:** https://www.dice.com/job-detail/9d2007e4-e3fc-4fab-8b6a-75ac44886d20

## About the Role

Snowflake Administration: Strong hands-on experience administering enterprise Snowflake platforms (Virtual Warehouses configuration, Zero-Copy Cloning, Time Travel, Data Sharing, RBAC, and cost monitoring).
Infrastructure as Code (IaC): Advanced proficiency in Terraform, with specific experience using the Terraform Snowflake Provider and AWS Provider.
Cloud Infrastructure (AWS): Solid background in core AWS services that integrate with data platforms (S3 storage integration, IAM roles/policies, KMS encryption, PrivateLink, Lambda, EKS/ECS).
Automation & Scripting: High proficiency in Python for DataOps automation, workflow orchestration, and interfacing with AWS/Snowflake APIs.
CI/CD & Version Control: Experience using Git and CI/CD tools (GitHub Actions, GitLab CI, Jenkins) for automated schema management, code deployments, and data infrastructure updates.
Data Security & Governance: Proven experience enforcing data security policies, data privacy compliance, and granular permissions management.

Preferred / Nice-to-Have Qualifications
SnowLogic / dbt: Experience managing dbt (data build tool) deployments, environment configurations, and orchestration within Snowflake.
Snowflake Certification: Snowflake SnowPro Core or SnowPro Advanced Architect/Administrator certification.
Containerization: Familiarity with Docker and container management for running DataOps utilities or orchestrators.

## Description

We are seeking an experienced DataOps Engineer with specialized expertise in Snowflake Administration to design, automate, and maintain our enterprise cloud data infrastructure. In this role, you will be the core custodian of our Snowflake Data Warehouse while bridging the gap between Data Engineering and DevOps. You will leverage AWS, Terraform, and Python to automate provisioning, manage access controls, optimize performance and compute costs, and streamline CI/CD release cycles across our enterprise data platform., Snowflake Platform Administration: Manage, configure, and administer multi-environment Snowflake accounts (workspaces, virtual warehouses, databases, roles, and resource monitors).
Automated Infrastructure (IaC): Use Terraform to provision and manage Snowflake resources (roles, privileges, databases, schemas, network policies) as well as underlying AWS cloud infrastructure.
Security, Access & Governance: Implement Role-Based Access Control (RBAC), row/column-level security, data masking, and network policies in Snowflake. Ensure integration with enterprise IAM/SSO providers.
Cost Optimization & Performance Tuning: Monitor and optimize Snowflake credit consumption, warehouse auto-suspend/scaling policies, query performance, and storage costs across business units.
Pipeline & Python Automation: Write Python scripts and build custom automation using Snowflake SDKs/drivers (or boto3 for AWS) to automate data loads, user management, environment replication, and operational tasks.
CI/CD & Data Reliability: Design and manage CI/CD pipelines to automate schema migrations, dbt model deployments, and data warehouse releases across Dev, Staging, and Production environments.
Cloud Integration & Monitoring: Maintain secure data pipelines and data ingestion paths between AWS services (S3, IAM, Glue, Lambda) and Snowflake. Set up automated logging and alerting for warehouse performance and data freshness.