Data Engineer

Andersen is hiring a Data Engineer for a project automating revenue reconciliation processes and enhancing financial data accuracy, transparency, and operational efficiency.

The customer is a global investment management firm providing tailored investment solutions to institutional and private clients. It combines financial expertise with long-term investment strategies to help clients achieve their objectives while adapting to changing market conditions. The organization focuses on innovation, responsible investing, and operational excellence, continuously enhancing its capabilities to deliver sustainable value and support long-term growth.

The project is focused on automating revenue reconciliation processes within a large-scale data platform initiative. It aims to ensure accurate and efficient reconciliation of payments received through external payment providers, including driver and courier balance top-ups and commission deductions, while improving financial data accuracy, transparency, and operational efficiency.

Responsibilities:

• Gathering and clarifying requirements from marketing analysts and BI, and turning them into changes to attribution logic, sources and data marts.

• Leading the migration of the attribution pipeline (dbt models, Airflow DAGs, sources) to the core DWH platform. Running old and new in parallel and reconcile them before switching over.

• Building and optimizing incremental data marts in BigQuery (dbt/SQL) and Airflow, including recalculations and backfills.

• Designing and implementing data quality checks and investigating discrepancies against product and source data.

• Performing deep-dive analysis of external inputs (AppsFlyer, ad network cost feeds, Google Sheets dictionaries, upstream marts) to keep data flowing reliably from source to consumption.

• Participating in testing, data validation and release processes, including repointing downstream consumers.

• Maintaining technical documentation for the domain and…