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 spreading knowledge across the team.

Requirements: - Experience as an Analytics Engineer / DWH Engineer / Data Analyst working with DWH for 3+ years. - Hands-on experience with data warehouses. - Strong understanding of DWH architecture and data layers (ODS, Data Marts). - Understanding of incremental loads, historical data handling and deduplication. - Expert SQL skills. - Experience designing and optimizing data marts. - Experience with BigQuery or similar columnar DB. - Experience with dbt on large incremental projects. - Experience migrating pipelines between platforms with data parity validation. - Experience with Airflow or a similar orchestration tool. - Knowledge of Python for data processing and ETL tasks. - Ability to work with stakeholders and translate business needs into data requirements. - Level of English – from Intermediate+ or above.

Nice to have: - Experience working with mobile and marketing attribution data using AppsFlyer, Adjust, or Branch, including ad network cost data, SKAN, and ATT. - Familiarity with ad fraud detection and analytics, particularly AppsFlyer Protect360. - Experience with GCP, including Cloud Storage and Dataform. - Experience with analytics and BI tools such as Lightdash, Looker, and Tableau.

Compensation: 1800–2950 EUR per month.