We are looking for a Business Intelligence Engineer / BI Developer to support financial systems and data products within the FinSys Data Platform team. This role will focus on building scalable, high-quality analytics solutions that enable Accounting, Finance, Payments, and Tax teams to gain actionable business insights.

The role is highly hands-on and requires strong programming capabilities, particularly in Python and SQL. In addition to building dashboards, this position will contribute to automated, AI-enabled analytics solutions that go beyond traditional BI, including agentic workflows and intelligent reporting built on top of Snowflake and modern data platforms.

• Design, build, and maintain BI dashboards and analytics solutions using Tableau and Tableau Prep.

• Develop automated reports, data pipelines, and analytical workflows using Python, leveraging Pandas, NumPy, and related libraries.

• Translate business and functional requirements into scalable technical solutions.

• Identify, validate, and integrate appropriate data sources to support financial analytics use cases.

• Expand and enhance finance data products within the solutions platform.

• Improve the quality, consistency, and reliability of financial datasets and reporting outputs.

• Work extensively with Snowflake to support analytics, billing solutions, and data transformations.

• Build and maintain AI-enabled and agentic analytics solutions, including production use of LLMs and prompt engineering to support reporting and insights generation.

• Develop a strong understanding of financial and product data across multiple systems to proactively surface insights and recommendations.

• Partner closely with cross-functional teams, including Accounting, Finance, Payments, and Tax.

• Communicate analytical findings clearly to non-technical stakeholders, ensuring insights are understandable and actionable.

• Validate data accuracy, challenge assumptions, and ensure analytical rigor across all deliverables.

• Strong SQL skills for querying and analyzing large datasets.

• Intermediate to advanced Python programming, with hands-on experience using Pandas and NumPy.

• Experience working with Snowflake as a primary data warehouse.

• Proven experience creating data visualizations and dashboards using Tableau or similar BI tools.

• Experience with data cleansing, transformation, and validation at scale.

• Solid understanding of reporting, descriptive statistics, probability, and large-dataset analysis.

• Hands-on experience with AI/ML technologies, including LLMs and prompt engineering in production environments.

• Strong ability to convert business questions into well-defined analytical and technical solutions.

• Comfortable working with multiple stakeholder groups to define metrics and success criteria.

• Willingness to challenge data quality, assumptions, and methodology.

• Ability to explain complex or technical concepts in clear, non-technical terms.

• Strong client-service mindset and collaborative approach.

• Adaptable and comfortable working in a fast-paced, evolving data environment.

• Proactive, detail-oriented, and solutions-focused.