Sr. Data Ops Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Data Ops Engineer based in Canada.

This role sits at the heart of a high-scale data and AI ecosystem, ensuring that critical data pipelines, integrations, and analytics platforms remain reliable, performant, and production-ready. You will be responsible for maintaining the health and stability of complex distributed data systems that power real-time insights across multiple business domains. Working in a collaborative, engineering-driven environment, you will partner closely with DevOps, data engineering, and business stakeholders to ensure data quality, observability, and operational excellence. The role combines strong engineering fundamentals with hands-on operational ownership of production systems. You will directly impact how data is ingested, processed, and delivered across the organization, enabling smarter decisions at scale. This is a highly visible role where reliability, performance, and precision are essential.

• Own the stability, performance, and reliability of production data pipelines, APIs, and data warehousing systems across multiple business domains.
• Serve as a primary responder for production incidents, diagnosing root causes, restoring services, and ensuring data integrity.
• Design, implement, and maintain monitoring, logging, and alerting systems to ensure full observability of data platforms.
• Manage, deploy, and optimize ETL/ELT pipelines and data integration workflows across cloud-based environments.
• Implement and enforce data quality, validation, and governance practices to ensure trustworthy downstream analytics.
• Collaborate with DevOps and infrastructure teams to support scalable AWS-based data platforms.
• Continuously improve performance, scalability, and efficiency of data processing systems and backend services.
• Maintain clear documentation, runbooks, and operational procedures for production systems and incident response.

Requirements:

• 5+ years of experience in Data Engineering, Data Operations, or SRE roles supporting production-scale data systems.
• Strong SQL skills for data analysis, troubleshooting, and validation.
• Proficiency in Python or similar scripting languages for automation and pipeline development.
• Hands-on experience with ETL tools such as Fivetran, dbt, Workato, or similar platforms.
• Strong knowledge of relational databases such as PostgreSQL, MySQL, or cloud RDBMS solutions.
• Experience with at least one major cloud provider (AWS, GCP, or Azure), ideally including serverless services.
• Familiarity with data warehouses such as Snowflake, BigQuery, Redshift, or Databricks.
• Strong understanding of CI/CD practices, DevOps workflows, and production monitoring tools.
• Experience with observability tools such as Datadog, Splunk, or CloudWatch.
• Strong troubleshooting mindset with the ability to manage complex distributed systems under pressure.
• Excellent communication skills and ability to work with technical and non-technical stakeholders in incident contexts.

Benefits:

• Competitive compensation package with base salary aligned to Canadian market standards.
• Equity opportunities and performance-based incentives (where applicable).
• Fully remote work flexibility within Canada.
• Comprehensive health, dental, and vision coverage.
• Paid parental leave and family support benefits.
• Professional development support and learning opportunities.
• Strong focus on engineering excellence and modern data technologies.
• Inclusive, collaborative, and high-ownership engineering culture.
• Wellness and mental health support programs.
• Opportunity to work on large-scale, real-world data systems with meaningful impact.