Senior Data Engineer, Back Market

• Technical Excellence: You possess extensive experience with Python and SQL, and have deep knowledge of data pipeline orchestration tools like Apache Airflow. Experience with BigQuery, Kafka, and event-driven architectures is highly valued. Icing on the cake if you've built production data architectures handling financial transactions with strict accuracy requirements on GCP
• Financial Domain Understanding: You're comfortable working with financial concepts like ledgers, reconciliation, revenue recognition, invoicing, and multi-currency transactions. You understand that financial data requires zero-tolerance for errors and strong auditability
• Software Craftsmanship: You follow best practices in software development, write testable code, and embrace continuous improvement. You understand the critical importance of data accuracy, monitoring, and comprehensive testing in financial systems
• Problem-Solving Mindset: You're flexible and creative in tackling complex data reconciliation challenges. You have a pragmatic approach to balancing technical debt versus features and cost versus scalability, while never compromising on financial data accuracy
• Team Player: You're well-organized, autonomous, rigorous, and thrive in distributed team environments with a strong collaborative spirit. You can clearly communicate technical concepts, data quality issues, and reconciliation results to both technical teammates and finance stakeholders (Accounting, FP&A, Payment teams)

Desirable

• We are looking for a Senior Data Engineer to help us build, scale, and maintain the data infrastructure behind Back Market's financial operations.
• You will design and implement data pipelines that ensure every euro, dollar, and pound is accurately tracked, reconciled, and attributed to the right party—enabling seamless financial operations for millions of transactions
• You will be working in an agile "build it and run it" environment where engineering teams build, launch, monitor, and support the products they own
• Money Ledger & Registrator: Scale the data pipelines that power our new ledger architecture, tracking all financial events and transforming them into accurate financial entities in our Money Journal
• Transaction Data Processing: Design, build & maintain ETL pipelines to collect, process, and reconcile financial data from multiple sources including payment providers, marketplace transactions, seller payouts, refunds, commissions, and service fees across multiple currencies and marketplaces (EU, US, APAC)
• Unmatched Money Product: Develop and enhance our automated reconciliation system that matches financial flows, identifies discrepancies, and serves as the single source of truth for accounting
• Financial Systems Integration: Build and maintain data flows between our internal systems and external financial tools (Microsoft Dynamics, Anaplan, payment processors) using tools like Fivetran and custom ETL pipelines
• Multi-Source Data Orchestration: Integrate data from internal systems (orders, payments, refunds) and external sources (banks, payment service providers, tax authorities) to provide a complete financial picture
• Financial Data Accuracy: Implement robust data validation, quality checks, and monitoring to ensure zero discrepancies in financial reporting—critical for accounting, audits, and regulatory compliance
• Reconciliation & Monitoring: Build automated reconciliation processes and dashboards (using BigQuery, Airflow, and Datadog) to detect and alert on data quality issues, missing transactions, or financial discrepancies
• Compliance & Audit Support: Support regulatory requirements such as DAC7 reporting, KPMG audits, e-invoicing compliance, and multi-jurisdiction tax reporting with accurate, auditable data pipelines
• Data Pipeline Orchestration: Design and maintain Airflow DAGs in GCP Cloud Composer to orchestrate complex financial data workflows, ensuring timely processing for critical month-end close and weekly payout cycles
• BigQuery Data Modeling: Build and optimize BigQuery data models and transformations (using dbt) that enable Finance, FP&A, and Accounting teams to perform analysis, reporting, and forecasting
• Real-time Financial Events: Work with Kafka streams to process financial events in near real-time, ensuring up-to-date balance tracking and reconciliation
• Explore new technologies and synchronize with the rest of Back Market ecosystem to make the Finance data pipelines evolve
• Participating in and advising on technical choices for finance-related data projects, working closely with Finance, FP&A, Accounting, Payment Operations, and business teams
• Building the new Ledger Registrator architecture and migrating financial flows from the legacy Badoom system to the new Money Ledger infrastructure
• Developing and maintaining the Unmatched Money reconciliation tool as the single source of truth for accounting, eliminating manual spreadsheet reconciliation
• Collecting, consolidating, and serving large volumes of financial transaction data across multiple currencies, marketplaces, and payment methods in BigQuery
• Automating critical financial processes such as weekly seller invoicing, month-end close data preparation, and regulatory reporting (DAC7, e-invoicing)
• Ensuring the scalability, security, stability, and availability of financial data systems with particular attention to data accuracy, audit trails, and compliance requirements
• Working closely with the Data Platform team to leverage shared infrastructure and with other MoJo teams (Payin, Payout, OMS) to ensure consistent financial data flows
• You'll be contributing to exciting projects such as;
• E-invoicing Compliance: Building infrastructure for French and EU electronic invoice requirements
• Trade-in to Finpay: Extending ledger capabilities to support new business models
• Unmatched Money evolutions: Making automated reconciliation the single source of truth for accounting
• Dynamic Pricing & Express Replacement: Supporting new marketplace features with financial data infrastructure
• Balance Adjustment Automation: Automating seller balance adjustments and reducing manual interventions

• TA Screening, 45 min
• Live challenge with 2 engineers, 60 min
• Data Knowledge interview, 45 min
• Technical leadership interview, 45 min
• Meet your Manager, 30 min
• Cultural fit, 45 min