DevOps Platform Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and sustain reusable engineering patterns, standards, templates, and guidelines for data product delivery across platforms such as dbt, Snowflake, GitLab, and others.

• Uphold coding quality practices, which include linting, formatting, naming conventions, merge request templates, and review expectations.

• Enhance and refine CI/CD workflows, integrating automated testing, validation, deployment gates, promotion logic, and release readiness checks.

• Oversee release and change management processes, encompassing deployment planning, dependency tracking, rollback planning, release notes, and post-release validation.

• Institutionalize observability and alerting standards for production pipelines, focusing on job health, freshness, failure rates, data quality checks, and operational dashboards.

• Assist in managing production incidents through triage, root-cause analysis, stakeholder communication, corrective measures, and runbook enhancements.

• Administer environment management practices across development, testing, and production phases, including configuration standards, promotion rules, and deployment consistency.

• Enhance the developer experience through comprehensive documentation, self-service guidance, automation, and optimized development, review, deployment, and support processes.

• Aid centralized and federated teams in embracing reusable patterns, quality standards, and operational practices that facilitate reliable data product delivery.

• Collaborate with technical data leaders to empower centralized and federated data teams to deliver trustworthy production data products consistently and effectively within the data mesh framework.

⛳️ Requirements

• Over 5 years of experience in Data Engineering, Analytics Engineering, DevOps, Platform Engineering, or a related technical field.

• Practical experience in supporting production data pipelines, data products, or analytics engineering workloads within an enterprise setting.

• Proficient working knowledge of Snowflake, SQL development, dbt, GitLab or comparable source control, and CI/CD workflows.

• Background in implementing or supporting automated testing, linting, validation, deployment checks, or maintaining code quality standards.

• Experience with release management, change management, deployment coordination, or ensuring production readiness.

• Knowledge of observability, alerting, monitoring, runbooks, and incident response for production systems or data pipelines.

• Ability to resolve complex issues related to pipelines, environments, dependencies, and data quality with minimal assistance.

• Excellent communication, documentation, collaboration, and problem-solving abilities.

• BA/BS degree in Information Science, Data Analytics, Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.

• Experience in supporting federated data teams, data mesh operational models, or business-owned data product delivery.

• Python development or scripting experience for automation, operational tooling, or production support.

• Experience with productionized Data Science, machine learning, or code-based data products.

• Familiarity with orchestration platforms such as Airflow, Composer, or similar tools.

• Understanding of AWS, GCP, data quality frameworks, lineage tools, data catalogs, observability platforms, or enterprise analytics platforms.

• Ability to comply with U.S. export controls.

🏝️ Benefits

• Eligibility for bonuses.

• Medical insurance benefits.

• Retirement plan benefits.

• Financial incentives.

• Wellness programs.

• Paid time off.

• Employee discounts.

• Reasonable accommodations during the recruitment process.