Data Engineer III
TD•Toronto, ON
•Onsite
About The Position
We are hiring a Senior FinOps Data & Automation Engineer to build the data, automation, and analytics foundation for an enterprise FinOps capability. This role will support cost transparency, allocation, forecasting, optimization, governance, and executive reporting across cloud, AI, data platforms, and broader technology consumption. The successful candidate will work closely with FinOps, Finance, Engineering Analytics, Cloud Engineering, Procurement, and Technology leadership to turn complex technology spend data into trusted, auditable, and actionable insights.
Requirements
- 5–10 years of experience in data engineering, analytics engineering, BI engineering, financial data analytics, or a related data-focused role.
- University degree in Computer Science, Data Engineering, Information Systems, Engineering, Mathematics, Finance, Business Analytics, or a related field.
- Strong experience with SQL, data modeling, ETL/ELT pipelines, and large complex datasets.
- Experience integrating data across multiple enterprise systems.
- Experience with data platforms such as Databricks, Snowflake, BigQuery, Azure Synapse, Microsoft Fabric, SQL Server, or similar tools.
- Experience with BI/reporting tools such as Power BI, Tableau, Looker, or similar platforms.
- Strong understanding of data quality, reconciliation, controls, lineage, documentation, and governance.
Nice To Haves
- Experience with Cloud FinOps, technology finance, infrastructure finance, FP&A, or cost management.
- Familiarity with Azure, AWS, or Google Cloud billing and usage data.
- Knowledge of cloud tagging, allocation, chargeback/showback, forecasting, reservations, savings plans, anomaly detection, and optimization tracking.
- Exposure to FOCUS billing data standard, unit economics, AI cost management, data platform economics, or software usage-based contracts.
- Experience in banking, financial services, regulated enterprises, or large technology organizations.
- Certifications in FinOps, Azure, AWS, GCP, Databricks, Power BI, or data engineering are assets.
Responsibilities
- Build and maintain FinOps data pipelines from ingestion through reporting and self-service analytics.
- Normalize cloud and technology spend data across provider feeds, including alignment to standards such as FOCUS where applicable.
- Integrate billing, usage, tagging, metadata, CMDB, application, owner, finance, contract, and vendor data.
- Support cost taxonomy, allocation rules, metadata standards, showback, chargeback, forecasting, and auditability.
- Create trusted datasets for cost reporting by business unit, product, application, environment, owner, platform, and vendor.
- Build analytics to support budget guardrails, variance reporting, anomaly detection, remediation workflows, and optimization tracking.
- Support commitment-based spend analysis, including reservation, savings plan, coverage, utilization, and waste reporting.
- Develop reporting for rightsizing, idle resource cleanup, quota tuning, license reclamation, and other optimization opportunities.
- Build models and dashboards for unit economics, TCO, ROI tracking, and business outcome-based cost analysis.
- Partner with Engineering Analytics to deliver enterprise dashboards, automated alerts, recommendations, and workflow automation.
- Ensure data quality, lineage, reconciliation, documentation, controls, and auditability across FinOps data assets.
- Reduce manual reporting and spreadsheet dependency through automation.
Benefits
- health and well-being benefits
- savings and retirement programs
- paid time off
- banking benefits and discounts
- career development
- reward and recognition programs
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What This Job Offers
Job Type
Full-time
Career Level
Senior
