Technology Business Engineer

About the role

The Technology Business Engineer administers and supports the Apptio platform, handling data integrations, cost models, allocation logic, reporting, and data‑quality controls. Working closely with the Technology Business Manager, FinOps, Finance and other stakeholders, the role delivers reliable, traceable, decision‑ready technology cost information.

Key responsibilities

• Administer Apptio environments, including configuration, user access, roles, permissions and operational settings.
• Operate and monitor recurring data ingestion, transformation, validation, calculation and publishing processes.
• Maintain cost models, allocation rules, hierarchies, reference data and approved business logic.
• Reconcile source‑system totals with Apptio inputs/outputs, documenting exceptions and corrections.
• Monitor data completeness, accuracy, timeliness, consistency and integrity across financial and operational datasets.
• Troubleshoot failed loads, calculation errors, mapping issues and reporting discrepancies.
• Build and maintain dashboards, reports, metrics and distribution processes.
• Support budgeting, forecasting, variance analysis, cost transparency and showback reporting cycles.
• Maintain integrations with financial, procurement, HR, project, asset, cloud and service data sources.
• Implement enhancements through controlled development, testing, documentation and release practices.

Required profile

• 10+ years of data engineering or related technical experience.
• Proven experience designing enterprise data solutions on cloud platforms (Azure, AWS) and modern data warehouses (Snowflake, Databricks).
• Strong background in infrastructure security, role‑based access controls, data governance and cross‑system integration.
• Experience with financial systems, cost modeling, budgeting and forecasting concepts.
• Ability to troubleshoot complex data, model, access and reporting issues.

Required skills

• Apptio administration (Cost Transparency, Planning)
• Cloud platforms: Azure, AWS
• Data warehouses: Snowflake, Databricks
• BI tools: Tableau, PowerBI, Sigma
• ETL/ELT design, streaming pipelines, workflow orchestration
• SQL and advanced data modelling
• DevOps practices: version control, CI/CD
• Data‑quality controls and governance