Sr. DevOps Engineer - Snowflake
New
P
phDataData and AI Consultancy
This role is based in the USA, Eastern and Central Time ZoneFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 6+ years
- Required Skills
- AWSPythonSQLETLSnowflakeAzureCI/CDLinuxDevOpsTerraform
Requirements
- 6+ years of experience in DevOps, cloud data platform operations, or production support.
- Working knowledge of SQL for writing, debugging, and optimizing queries.
- Operational support experience for cloud-native data warehouses such as Snowflake or Amazon Redshift.
- Hands-on experience with Relational Database Management Systems (Oracle or MS SQL Server).
- Experience supporting scheduled production data jobs and pipelines.
- Working knowledge of Unix/Linux environments and system administration.
- Proficiency in writing and optimizing Python for automation.
- Experience with cloud services on AWS or Azure (S3, ADLS, Azure Data Factory).
- Familiarity with ITIL processes and SLA-driven support environments.
- Active daily use of AI coding tools like Cursor, GitHub Copilot, or Claude.
- Familiarity with CI/CD tooling and infrastructure-as-code tools such as Terraform.
- Strong English verbal and written communication skills.
- Experience delivering projects in a consulting or professional services environment.
Responsibilities
- Own and drive end-to-end operational support and incident management for modern cloud data platforms including Snowflake, AI workloads, and data lakes.
- Monitor and support production ETL/ELT pipelines, ensuring timely resolution of failures.
- Perform deep root-cause analysis and implement preventative measures for production processes.
- Collaborate with data engineering, architecture, and client stakeholders to deliver successful engagements.
- Provide technical leadership during incident bridges, design reviews, and runbook creation.
- Contribute to internal operational playbooks, automation scripts, and monitoring standards.
- Mentor junior engineers and share best practices across the team.
- Use AI tools daily to accelerate troubleshooting, documentation, and automation tasks.
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