- Position: Data Architect
- Location: Toronto, ON
- Duration: 6+ Months Contract to hire

Key responsibilities:

- Own the backend data infrastructure supporting the reporting platform.
- Bring new data sources into the environment and build the ingestion/integration process.
- Understand schemas, tables, columns, relationships and transformations.
- Combine multiple data sources when the business needs a consolidated view.
- Understand when data should be separated versus aggregated.
- Build and maintain data pipelines and automation.
- Own deployment and make sure pipelines and processes continue running reliably.
- Troubleshoot data-quality and data-lineage problems upstream.
- Recognize anomalies—for example, "Yesterday this showed $1M and today it shows $2M; that doesn't make sense"—and trace the problem back through the pipeline.
- Understand how the database ultimately supports the dashboards and reporting layer.
- Integrate new vendors/data feeds and their telemetry into the platform.
- Understand the overall architecture, rather than only the individual coding task assigned to them.
- Translate a business request into the technical work required to deliver the data.
- The critical differentiator
- They do not want an engineer who has to be handed a Jira story and told exactly what to build.
- 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.

Required Skills:

- 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.
- Solid 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.

Pay: $80.00-$90.00 per hour

Experience:

- AI: 3 years (preferred)
- Own the backend data infrastructure support report platform: 10 years (preferred)
- SQL, Data Modeling: 10 years (preferred)
- Data Engineering: 10 years (preferred)
- Financial Data Analytics: 10 years (preferred)
- ETL/ELT Pipelines, and Large Complex Datasets: 10 years (preferred)
- Data Platforms such as Databricks, Snowflake, BigQuery: 10 years (preferred)
- Power BI, Tableau, Looker: 10 years (preferred)
- Data Quality, Reconciliation, Controls, Lineage, Governance: 10 years (preferred)

Work Location: In person

📌 Data Architect (Toronto)
🏢 IT Accel
📍 Toronto