DevOps Platform Engineer

Meet the Moment with Alteryx We're living through a once-in-a-generation shift in how work gets done. Data, automation, and AI are quickly becoming the center of every business decision - and Alteryx is leading the transformation. You'll be working on the challenges that sit at the heart of modern business. No matter your role, the work you do will help organizations move faster, see more clearly, and tackle questions that used to feel impossible. If you're ready to meet the moment with innovation, curiosity, and excellence, there's a place for you here. Alteryx is searching for a DevOps Platform Engineer . This position is remote-friendly. Position Overview: As a DevOps Platform Engineer within Data Platforms, you will strengthen the standards, automation, and operational practices that enable reliable data product delivery across our enterprise data ecosystem. This role focuses on how data products are developed, tested, reviewed, deployed, monitored, and supported across dbt, Snowflake, GitLab, and related platforms. You will partner with technical data leads to implement and maintain engineering standards that enable centralized Data Engineering, Analytics Engineering, Data Science, and federated Data Ops business teams to deliver trusted production data products consistently and efficiently within our data mesh model. Success in this role means improving engineering consistency, reducing operational friction, increasing release confidence, and helping teams deliver trusted, maintainable data products at scale. Primary Responsibilities: Implement and maintain reusable engineering patterns, standards, templates, and guardrails for data product delivery across dbt, Snowflake, GitLab, and related platforms. Maintain code quality practices, including linting, formatting, naming conventions, merge request templates, and review expectations. Implement and improve CI/CD workflows, including automated testing, validation, deployment gates, promotion logic, and release readiness checks. Coordinate release and change management activities, including deployment planning, dependency tracking, rollback planning, release notes, and post-release validation. Operationalize observability and alerting standards for production pipelines, including job health, freshness, failure rates, data quality checks, and operational dashboards. Support production incidents through triage, root-cause analysis, stakeholder communication, corrective actions, and runbook improvements. Maintain environment management practices across development, test, and production, including configuration standards, promotion rules, and deployment consistency. Improve developer experience through documentation, self-service guidance, automation, and streamlined development, review, deployment, and support processes. Support centralized and federated teams in adopting reusable patterns, quality standards, and operational practices that support trusted data product delivery. Qualifications: 5+ years of experience in Data Engineering, Analytics Engineering, DevOps, Platform Engineering, or a related technical discipline. Hands-on experience supporting production data pipelines, data products, or analytics engineering workloads in an enterprise environment. Strong working experience with Snowflake, SQL development, dbt, GitLab or similar source control, and CI/CD workflows. Experience implementing or supporting automated testing, linting, validation, deployment checks, or code quality standards. Experience with release management, change management, deployment coordination, or production readiness practices. Familiarity with observability, alerting, monitoring, runbooks, and incident response for production systems or data pipelines. Ability to troubleshoot complex pipeline, environment, dependency, and data quality issues with minimal guidance. Strong communication, documentation, collaboration, and problem-solving skills. BA/BS degree in Information Science, Data Analytics, Computer Science, Software Engineering, a related technical field, or equivalent practical experience. Valued Skills: Experience supporting federated data teams, data mesh operating models, or business-owned data product delivery. Python development or scripting experience for automation, operational tooling, or production support. Experience supporting productionized Data Science, machine learning, or code-based data products. Experience with orchestration platforms such as Airflow, Composer, or similar tools. Familiarity with AWS, GCP, data quality frameworks, lineage tools, data catalogs, observability platforms, or enterprise analytics platforms. Compensation: Alteryx is committed to fair, equitable, and transparent compensation. Final compensation will be determined by various factors such as your relevant work experience, education, certifications, skills, and geographic location. The salary range for this role in the United States is $139,475 - $153,900. In addition, you may be eligible for additional compensation, such as a bonus. Employees may also be eligible for a wide range of other benefits, including medical, retirement, financial, wellness, time off, employee discounts, and others. Interested? Learn more and apply today at alteryx.com/careers! #LI-EM1 #LI-REMOTE Find yourself checking a lot of these boxes but doubting whether you should apply? At Alteryx, we support a growth mindset for our associates through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences . Benefits & Perks: Alteryx has amazing benefits for all Associates which can be viewed here . For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Alteryx will consider for employment qualified applicants with arrest and conviction records. This position involves access to software/technology that is subject to U.S. export controls. Any job offer made will be contingent upon the applicant’s capacity to serve in compliance with U.S. export controls.