Senior Analyst - Finance & Order Management
ExternalPrepare for this interview
EliteAI-generated questions, company research, and talking points tailored to this role
About the role
Design, develop, and maintain scalable data products and pipelines that support finance and order management processes, including order lifecycle tracking, revenue recognition, billing, and reconciliation. Partner with stakeholders across Finance, Order Management, and Engineering to translate business processes (e.g., order-to-cash, invoicing, etc.) into robust, reliable data models and pipelines. Architect and optimize data platforms (data lakes, warehouses, and streaming pipelines) to enable accurate, timely, and auditable financial and operational reporting. Build and operationalize data models and transformations that ensure consistency between order systems and financial systems, enabling trusted KPIs. Lead the development of scalable, automated data processes that strengthen data integrity, support efficient reconciliation, and enable proactive anomaly detection across finance and order management domains. Implement and enforce data governance, lineage, and security standards, ensuring compliance with financial regulations and audit requirements. Enable advanced analytics by preparing curated datasets that support financial reporting, operational insights, and decision-making. Communicate complex data concepts clearly to both technical and non-technical stakeholders, particularly within finance and operations teams. Act as a bridge between business and engineering, ensuring that data solutions accurately reflect financial logic and operational realities. About you: Bachelor's degree in Computer Science, Engineering, Statistics, Innovation Economics or a related field. 5+ years of experience designing, building, and operating scalable data solutions, with a focus on enabling reliable business processes and data-driven decision-making. Expertise in SQL, with a proven ability to model data that supports financial reporting, order lifecycle tracking, and operational performance analysis. Hands-on experience with cloud-based data platforms, particularly within Google Cloud Platform (e.g., BigQuery, Pub/Sub, Cloud Functions), or similar ecosystems, to deliver scalable data solutions for business-critical use cases. Proven experience with modern data warehousing technologies such as Snowflake, BigQuery, or Redshift, including building trusted, business-facing data models that serve finance, operations, and analytics teams. Solid experience with dbt (Data Build Tool) to transform raw data into well-governed, reusable data products aligned with business definitions and KPIs. Proficiency in at least one programming language (e.g., Python, Java) to develop robust data pipelines and automation supporting operational and financial workflows. Experience ensuring data quality, consistency, and reconciliation, ideally within finance and order management Ability to translate business requirements into technical solutions and collaborate effectively with stakeholders across Finance, Order Management Operations, and Analytics. Experience with data visualization tools (e.g., Tableau, Power BI, Looker) to support business reporting and insight generation.