Associate Site Reliability Engineer (Devops + K8s + Data Warehouse-Snowflake)

Job Title:  Associate Site Reliability Engineer 

Acquia is the open source digital experience company. We provide the world's most ambitious brands with technology that allows them to embrace innovation and create customer moments that matter. At Acquia we believe in the power of community and collaboration – giving our customers the freedom to build tomorrow on their terms.
Headquartered in Boston, we have been named as one of North America’s fastest growing software companies as reported by Deloitte and Inc. Magazine, and have been rated a leader by the analyst community and named one of the Best Places to Work by the Boston Business Journal. We are Acquia. We are building for the future of the web, and we want you to be a part of it.

Site Reliability Engineering (SRE) is what you get when you treat operations as if it's a software problem. Our mission is to improve, maintain, and provide for the software and systems behind all of Acquia's services – with an ever-watchful eye on their availability, latency, performance, and capacity.

As an Associate SRE, you will be working on ensuring the reliability and performance of our data infrastructure, including Snowflake data warehouses, data pipelines on Kubernetes, and analytics systems, while coding in Python and exploring AI-powered automation to enhance data platform reliability.

As an Associate Site Reliability Engineer, you will…

• Work in an Agile team designing, writing and delivering software to improve the availability, scalability, performance, and efficiency of Acquia's data infrastructure and pipelines
• Develop and maintain monitoring, alerting, and observability solutions for Snowflake data warehouses, Dagster pipelines, and data processing workflows
• Build automation tools using Python and infrastructure-as-code technologies to ensure reliable data pipeline operations and reduce manual overhead
• Explore and implement AI-driven solutions for data quality monitoring, pipeline anomaly detection, and automated data infrastructure scaling
• Collaborate with Data Engineering teams to implement reliability best practices for data pipelines including SLI/SLO definition for data freshness and quality
• Monitor and optimize Snowflake performance, cost efficiency, and resource utilization across multiple environments
• Participate in on-call rotations for data infrastructure incidents, contributing to post-incident reviews and reliability improvements
• Build and enhance CI/CD pipelines for data pipeline deployments with automated testing and rollback capabilities
• Ensure data infrastructure security, access controls, and compliance monitoring across all data systems
• Contribute to the evolution of our data platform SRE practices and tooling standards

What you'll need to be successful:

• 1-3 years of experience in SRE or DevOps Engineer and data engineering roles
• Experience with data warehouse technologies (Snowflake preferred) and understanding of data pipeline architectures
• Familiar with container based products like docker and kubernetes
• Programming or Scripting exp in Python for automation, data pipeline tooling, and system integration
• Experience with Infrastructure as Code tools (Terraform, Ansible) for data infrastructure management
• Hands-on experience with data monitoring and observability tools (DataDog, Snowflake monitoring, or similar data-focused tools)
• Knowledge of cloud platforms (AWS, GCP, Azure) with focus on their data services (S3, BigQuery, etc.)
• Understanding of CI/CD principles for data pipeline deployments and data platform operations
• Strong problem-solving skills and systematic approach to troubleshooting data systems and pipeline issues
• Ability to work collaboratively with Data Engineering teams and communicate effectively about data reliability
• BS degree in Computer Science or related technical field, or equivalent practical experience

Extra credit if you:

• Have experience implementing SLIs (Service Level Indicators) and SLOs (Service Level Objectives and error budgets for data pipelines and data freshness/quality metrics
• Interest in AI/ML applications for data quality monitoring, pipeline automation, and intelligent data operations
• Interest in exploring MLOps infrastructure and AI-powered data platform reliability challenges
• Knowledge of data workflow orchestration tools (Dagster, Airflow, Prefect) and their operational challenges
• Experience with data quality frameworks and automated data validation systems
• Familiarity with Snowflake administration, performance tuning, and cost optimization
• Contributions to open-source data infrastructure or data reliability tools and communities
• Understanding of data governance, lineage tracking, and compliance automation for data systems
• Experience with incident management for data pipeline failures and data quality issues

We are an organization that embraces innovation and the potential of AI to enhance our processes and improve our work. We are always looking for individuals who are open to learning new technologies and collaborating with AI tools to achieve our goals.

Acquia is proud to provide best-in-class benefits to help our employees and their families maintain a healthy body and mind. Core Benefits include: competitive healthcare coverage, wellness programs, take it when you need it time off, parental leave, recognition programs, and much more!

Individuals seeking employment at Acquia are considered without regard to race, color, religion, caste, creed, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation. Whatever you answer will not be considered in the hiring process or thereafter.