Business Intelligence Engineer

Summary

Join Tala, a leading fintech company, as a Business Intelligence Engineer and contribute to building and maintaining critical data infrastructure to support stakeholder data needs. You will work closely with both technical and non-technical stakeholders, translating business needs into data requirements. This role involves building and refining ad-hoc reports, designing a sustainable reporting infrastructure, and collaborating with Data and Engineering partners. You will be responsible for data reconciliation, identifying discrepancies, and working with business users to understand their analytical needs. Tala offers a remote-first approach with offices globally and a mission-driven culture.

Requirements

• 2-5 years of relevant experience and BS in Computer Science, Information Management, Engineering, Statistics or related fields
• Strong SQL and Python skills and experience with building data infrastructure to support reporting and analytical needs
• Strong experience with working with queries and pipelines that involve multiple data sources, functions, and systems
• Experience with data warehouses and ETL/data transformation pipelines
• Adept at queries, report writing and presenting findings
• Adept at writing ad-hoc QA queries to find issues with data and conducting data QA and reconciliation
• Experience with digging into underlying data and identifying discrepancies and business logic
• Strong communication skills with the ability to influence in a dynamic, cross-functional environment; customer-focused, with strong history of driving results, managing complexity and dealing with ambiguity

Responsibilities

• Working with stakeholders and understanding product changes in order to update or build new data infrastructure
• Build and maintain data infrastructure in the Snowflake warehouse to support reporting and analytical needs
• Creating and maintaining views, tables, and functions in the Snowflake warehouse
• Using ETL tools to automate data updates and reporting e.g DBT, Python, etc
• Providing both ad-hoc and scheduled reporting to Finance and Accounting teams
• Identifying discrepancies and reconciling between data sources to ensure data integrity
• This includes conducting deep dives and complex data reconciliation investigations
• Collaborate with Data and Engineering to build sustainable reporting to enable better and faster reports and infrastructure (e.g. custom analytics tools, dashboards, and financial reports); report on weekly / monthly operational, business and financial performance
• Work with business stakeholders, Data and Engineering teams to validate data, identify gaps and contribute to changes in business processes and data pipelines to fix data gaps and to develop long-term solutions
• Work with non-technical business users to understand their analytical needs, document and prioritize requirements, and help them effectively use the data and analytical tools that the team has developed

Benefits

Remote-first approach