Number of Openings:1
Worker Type:Permanent
Position Overview:Data is deeply embedded in the product, engineering, analytics, and operational culture at Finning.
Finning Canada is looking to hire a permanent, fulltime Data Engineer II based either in Surrey, Calgary or Edmonton who will work as a part of the Software Development Services (SDS) Tier 4 support team, you will provide advanced production support for reliable, scalable, secure, and AI-ready data solutions. This role is focused on monitoring, troubleshooting, incident resolution, service request fulfilment, operational readiness, and continuous improvement across modern data processing and storage platforms, including Snowflake, Databricks, Azure Data Factory, Azure Data Lake, and SQL.
You will work closely with product, engineering, analytics, infrastructure, security, and business teams to keep critical data services stable, performant, secure, and supportable.
Job Description:Responsibilities- Provide Tier 4 production support for data platforms, pipelines, integrations across Snowflake, Databricks, Azure Data Factory, Azure Data Lake, and SQL databases.
- Triage, investigate, resolve, and document incidents, service requests, defects, data quality issues, performance problems, failed jobs, and access-related requests.
- Support Snowflake operations including databases, schemas, warehouses, roles, access patterns, query troubleshooting, performance tuning, cost awareness, secure data sharing, and operational governance.
- Perform root cause analysis, contribute to problem management, and recommend preventive actions to reduce recurring incidents and improve service reliability.
- Create and maintain support documentation, runbooks, knowledge articles, recovery procedures, escalation paths, and operational handover materials.
- Use AI-assisted tools responsibly to accelerate support activities such as log analysis, query troubleshooting, documentation, ticket summarization, anomaly detection, and knowledge discovery while maintaining privacy, security, and quality standards.
- Collaborate with development and engineering teams on fixes, releases, change validation, operational acceptance, deployment readiness, and post-release support.
- Drive continuous improvement in monitoring, alerting, automation, support processes, incident response, access management, data quality checks, and operational stability.
We'd love to hear from you if you have - At least 4 years of practical experience development and/or supporting production data platforms, data pipelines, integrations, and operational data services using Snowflake, Databricks, Azure Data Factory, Azure Data Lake, SQL, and modern ELT/ETL patterns.
- Hands-on experience troubleshooting Snowflake workloads, including SQL queries, warehouses, schemas, roles, permissions, performance, data loads, and operational failures.
- Strong SQL skills with the ability to investigate data discrepancies, failed jobs, slow queries, access issues, and production incidents.
- Experience working with monitoring, alerting, logging, job scheduling, data quality checks, and operational dashboards for data platforms and pipelines.
- Good understanding of support practices including incident management, request fulfilment, change support, problem management, root cause analysis, escalation, and knowledge management.
- Working knowledge of Python, PySpark, scripting, Git, CI/CD concepts, and automation practices sufficient to troubleshoot and support production data solutions.
- Awareness of how AI can be used responsibly to improve data support activities, including ticket triage, log analysis, anomaly detection, documentation, and operational knowledge discovery.
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or equivalent practical experience.
- Excellent communication skills, strong ownership, customer focus, analytical troubleshooting ability, attention to detail, and a proactive team-oriented mindset.
