Senior Staff Data Ops Engineer (Canada)

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Requirements:

• 13+ years of experience in engineering, with at least 5+ years in data engineering, data ops, or related roles.
• Proven experience in designing and implementing data architectures, ETL processes, and DevOps pipelines.
• Expertise in cloud platforms (AWS, Azure, or GCP) and cloud-native solutions.
• Strong understanding of data governance, security, and compliance standards (e.g., GDPR, HIPAA).
• Proficiency in programming and scripting languages (e.g., Python, Java, Bash).
• Experience with modern DevOps tools such as Kubernetes, Docker, Terraform, Jenkins, or similar.
• Track record of successfully managing and scaling high-performing technical teams.
• Experience with big data technologies (e.g., Kafka).
• Familiarity with ML/AI infrastructure and frameworks.
• Hands-on experience with both relational and non-relational databases (e.g., SQL, NoSQL).
• Certifications in cloud platforms or DevOps practices are a plus.
• You have maintained data management systems and have built new data pipelines from scratch.
• You are comfortable automating data flows with resilient code using Python.
• Experience with Dagster or other data orchestration platforms such as Airflow.
• You have strong database architecture design and management knowledge in both structured and unstructured data.
• Advanced knowledge of Elasticsearch or OpenSearch, including configuration, operation, and using for search
• Extensive experience working with SQL, SQLAlchemy with Postgres, Athena, Parquet and Iceberg.

Responsibilities:

• Develop and execute the long-term vision for the organization’s data engineering and DevOps strategies.
• Collaborate with senior leadership to prioritize initiatives, set objectives, and define measurable outcomes.
• Stay ahead of industry trends, tools, and technologies to ensure competitive advantage and efficiency.
• Build, mentor, and lead a diverse team of data engineers and DevOps professionals.
• Foster a culture of innovation, accountability, and collaboration within the team.
• Establish best practices for performance management, career development, and skills growth.
• Oversee the design, development, and maintenance of scalable data pipelines, warehouses, and processing frameworks.
• Build the infrastructure and codebase required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
• Drive the implementation of best practices in data governance, quality, and security.
• Ensure the availability, reliability, and performance of data systems
• Lead the adoption of modern DevOps methodologies to streamline CI/CD pipelines and deployment processes.
• Ensure robust monitoring, logging, and alerting systems are in place for all applications and data infrastructure.
• Partner with cross-functional teams, including product, analytics, and engineering, to understand and deliver on business needs.
• Present project updates, performance metrics, and strategic initiatives to leadership.