25 legal entities, one reporting layer

Senior FP&A Analyst, World Kinect, Oslo, Dec 2023 to Jul 2026

Context

A group with 25 legal entities across APAC, EMEA and North America. Its data sat in three CRMs, two ERPs and two contract management systems. Management reports arrived about 10 days after month-end close. The numbers were pulled by hand from the systems, then reconciled manually. My work covered the renewable energy side, long-term energy contracts and the US gas business.

What I did

Designed the data model and built the integration layer, together with the finance team, that brought those systems into one governed reporting platform.
Python ingestion into Snowflake, medallion-style data layers, data marts for Power BI.
Defined master data standards. Traced reporting discrepancies to their root cause and fixed them in the data model, not in the reports.
Only part of the group sat in Oracle FCCS, so I built a separate consolidation and reporting layer in Snowflake covering the full entity perimeter.
Automated reconciliations and re-engineered the month-end close and variance analysis workflows.
Replaced Excel-based processes with BI reporting embedded in existing leadership routines.
Built a time tracker and rolled it out to the consulting department, including training the people who use it. Before, the department set project completion by estimate. Now logged hours drive the revenue accruals automatically and show profitability by client.

My role

I built the data model, pipelines, dashboards and the time tracker, and trained its users. My manager handled communication with the commercial teams.

Result

Management reporting moved from 10 days after close to a daily refresh.
Extracts from several systems and manual reconciliations were replaced by one governed source.
Management P&L by entity, region and business line, drillable to transaction level and tying to the statutory accounts.
Revenue accruals for consulting projects come from logged time instead of estimates, and profitability by client is visible.

Stack

Snowflake, SQL, Python, Power BI, Oracle FCCS