Senior FinOps Data Engineer

A major focus will be building a central AI Cost and Usage Data Product, providing visibility across consumption, attribution, forecasting, invoice reconciliation and optimisation., You will take ownership of the technical delivery of FinOps data products, working closely with Cloud, Data, Finance, Procurement, Security and Architecture teams., * Design and build data pipelines for cloud, AI and data-platform cost and usage

• Ingest and reconcile billing, invoice, pricing and consumption data across Azure, AWS, Snowflake and AI platforms
• Build robust ELT/ETL pipelines using Python and SQL
• Develop canonical data models for multi-provider cost and consumption data
• Build attribution models across accounts, subscriptions, applications, projects, cost centres and business units
• Reconcile granular usage data against invoices and contracted pricing
• Develop telemetry to identify optimisation opportunities, anomalies, waste and inefficient consumption
• Build governed Power BI semantic models and reporting
• Work with Finance and Procurement on forecasting, commitments, pricing and realised savings
• Establish data quality, testing, lineage, monitoring and engineering standards
• Help engineering and platform teams understand the economics of their cloud and AI consumption

You will be an experienced Data Engineer with strong hands-on technical skills and experience working with complex cloud cost and usage datasets.

Key experience:

• Advanced SQL and Python
• Strong production data engineering experience
• Data modelling, schema design and ELT/ETL
• Snowflake engineering and cost optimisation
• Azure Cost Management, resource and usage data
• AWS billing and cost data, including CUR / Cost Explorer
• REST APIs, logs, object storage and enterprise data integrations
• CI/CD, automated testing, source control and observability
• Experience reconciling usage and consumption data against invoices
• Understanding of FinOps, including allocation, showback/chargeback, forecasting, anomaly management, unit economics and optimisation
• Ability to independently lead a complex technical workstream

Experience within a large financial services or regulated enterprise environment would be advantageous.

Particularly valuable experience

We would be particularly interested in candidates with experience of:

• AI / GenAI cost and consumption data
• Token-based usage and cost attribution
• OpenAI, Azure OpenAI or other AI provider telemetry
• FinOps FOCUS standards
• dbt
• Power BI / DAX
• Terraform or other Infrastructure as Code
• FinOps certification

This is an excellent opportunity for a senior engineer who wants to work at the intersection of Data Engineering, FinOps, Cloud and AI, helping a major organisation understand exactly where its technology spend is going and how that spend can be optimised., * Data Engineering: 5 years (required)

• Python & SQL: 5 years (required)
• building cloud cost & billing data pipelines: 1 year (required)
• Azure, AWS & Snowflake cost/usage data: 1 year (required)
• forecasting & cloud cost optimisation: 1 year (required)
• reconciling granular cloud usage: 1 year (required)