Staff Data Engineer building scalable pipelines and lakehouse architecture for Sonatype, a software supply chain security company. Driving trusted analytics, ML, and business intelligence data with Databricks, Spark, and modern cloud technologies.
About the role
- Data Engineer II at Finning supporting production data platforms and integrations using Snowflake, Databricks, Azure services. Collaborating with teams to ensure operational stability and reliability.
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.
Requirements
- At least 4 years of practical experience developing 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.
Benefits
- Competitive compensation: $80,000 – $95,000 base + bonus + benefits
- Global exposure across treasury, capital markets, and risk
- Strong career progression opportunities within finance
- Collaborative, supportive, and high-performing team
- Hybrid work model: 2-to-3 days/week in office
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