Data Engineer II, Financial Intelligence

At Chewy, Financial Intelligence is building trusted, scalable, and well-governed data solutions that enable Finance and Accounting teams to make faster, more informed decisions. We are seeking an experienced Data Engineer II to design, develop, and maintain the data models and pipelines that support financial reporting, analytics, planning, and operational decision-making across the enterprise.

In this role, you will focus on transforming complex financial and operational data into reliable, well-structured, and reusable data models using dbt Cloud and Snowflake. You will work closely with Finance, Accounting, Analytics, and other business partners to understand business processes, define requirements, and translate those needs into scalable technical solutions and trusted data products.

The ideal candidate brings strong SQL, dbt, Snowflake, and data modeling expertise, along with the ability to work directly with business users and explain technical concepts in clear business terms. This is an opportunity to strengthen Chewy’s Financial Intelligence data foundation, improve the consistency and usability of financial data, and help Finance and Accounting teams access trusted information more efficiently.

What You’ll Do:

• Design, develop, and maintain scalable data models in dbt Cloud and Snowflake that support Finance, Accounting, reporting, planning, and analytical use cases.
• Partner directly with Finance, Accounting, and business stakeholders to understand business processes, reporting requirements, data definitions, and analytical needs.
• Translate business requirements into well-designed, reusable, and maintainable dimensional, fact, aggregation, and analytical data models.
• Build and support ETL/ELT processes that transform source data into trusted analytical datasets, with a primary emphasis on transformation and modeling.
• Implement data quality controls and validation to ensure the accuracy, completeness, consistency, and reliability of financial data.
• Investigate and resolve data discrepancies, reporting issues, transformation failures, and differences between source systems and downstream financial reporting.
• Optimize SQL and dbt models for performance, maintainability, scalability, and cost efficiency while documenting model dependencies, transformations, and metric definitions.
• Identify opportunities to simplify data transformations, reduce manual Finance processes, improve self-service access to trusted data, and apply practical automation where it adds value.

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Finance, or a related field, or equivalent practical experience.
• 5+ years of experience in data engineering, analytics engineering, business intelligence engineering, or a related data discipline.
• Strong proficiency in SQL, including experience developing complex transformations and analytical data models.
• Strong hands-on experience with dbt, including model development, testing, documentation, dependencies, reusable components, and development best practices.
• Experience working with Snowflake or a similar cloud data warehouse.
• Strong understanding of dimensional data modeling, including fact tables, dimensions, grain, relationships, slowly changing dimensions, and reusable analytical datasets.
• Demonstrated experience working directly with business users and analysts to gather requirements, validate solutions, troubleshoot data issues, and explain technical concepts in business terms.
• Experience supporting Finance, Accounting, FP&A, financial reporting, or other financial data domains preferred, with strong analytical, communication, documentation, and stakeholder partnership skills.