To succeed in the Tipalti interview process, you must prepare to demonstrate a blend of technical expertise, structured problem-solving, and clear communication. The hiring team looks for candidates who can go beyond the "what" of data and explain the "so what" and "now what."

Role-Related Knowledge – You must demonstrate advanced proficiency in SQL and Excel, as these are the primary tools used in the daily workflow and the technical assessments. Be prepared to write clean SQL code on the spot and manipulate large datasets efficiently.

Business Acumen – Tipalti is a fintech company, meaning you need to understand core financial concepts such as payment flows, transaction volumes, and customer retention. You should be ready to analyze data through a business lens, identifying how technical metrics translate into financial impact.

Structured Communication – Whether presenting your findings from a take-home test or answering behavioral questions, you must structure your thoughts logically. Use frameworks like the STAR method (Situation, Task, Action, Result) for behavioral questions, and start with the executive summary when presenting data.

Resilience and Focus – The interview process is rigorous and may include timed on-site tests. Demonstrating that you can maintain your focus, manage your time effectively, and deliver high-quality work under pressure is key to standing out.

The interview process for a Data Analyst at Tipalti is thorough and designed to evaluate both your technical execution and your strategic thinking. The process typically takes between three to six weeks to complete, depending on the location and candidate pipeline.

The journey begins with an initial phone screening with an HR representative, which focuses on your background, motivation, and cultural alignment. This is followed by a conversational interview with the hiring manager to discuss your analytical experience and dive deeper into your technical background. The core of the evaluation lies in the practical assessment stage, which involves a multi-part technical test that simulates real-world challenges you would face on the job.

This visual timeline illustrates the typical progression of the interview stages. Candidates should use this overview to pace their preparation, ensuring they allocate sufficient time to practice hands-on SQL and Excel analysis before reaching the practical assessment stage. While the exact order of interviews may vary slightly by region, the technical and behavioral evaluations remain highly consistent.

SQL Proficiency

SQL is a fundamental tool for any Data Analyst at Tipalti. The technical assessment will evaluate your ability to write structured, readable, and optimized queries to extract specific business metrics from relational tables.

Be ready to go over:

• Common Table Expressions (CTEs) – Using WITH clauses to structure complex queries and break down calculations into logical steps.
• Aggregate and Window Functions – Calculating running totals, moving averages, and percentages of totals across different partitions.
• Data Filtering and Joining – Correctly utilizing various join types to merge transactional tables with customer dimension tables without losing or duplicating data.
• Advanced concepts (less common) – Query optimization techniques, index utilization, and handling nested JSON data fields within relational databases.

Example questions or scenarios:

• "Write a SQL query using a CTE to calculate the monthly percentage contribution of each payment method to the total transaction volume."
• "How would you write a query to identify the top 5 customers by transaction volume for each country in the last quarter?"

Business Data Analysis & Presentation

A core part of the Tipalti interview is the practical test, which often includes analyzing a large Excel dataset containing around 400,000 rows of company data. You will be expected to explore this data, identify trends, and present your findings clearly.

Be ready to go over:

• Data Cleaning and Preparation – Handling missing values, filtering out noise, and structuring large datasets for analysis in Excel.
• Pivot Tables and VLOOKUP/XLOOKUP – Summarizing massive amounts of transactional data efficiently to find key business drivers.
• Product Analysis (MP vs. AP) – Understanding the distinct business dynamics between the Marketplace Portal (MP) and Accounts Payable (AP) functions.
• Advanced concepts (less common) – Building dynamic dashboards in Excel, using advanced statistical formulas, or leveraging Power Query for data transformation.

Example questions or scenarios:

• "Analyze this 400K-row dataset of platform transactions and present the three most critical insights regarding payment failure rates."
• "Compare the user activity trends on the Marketplace Portal against the Accounts Payable portal and recommend where the product team should focus their optimization efforts."

Behavioral & Collaboration

Tipalti values collaborative problem-solvers who can work effectively across engineering, product, and business teams. This area evaluates how you handle feedback, manage stakeholders, and align with company values.

Be ready to go over:

• Stakeholder Management – Translating technical data insights into actionable business recommendations for non-technical partners.
• Prioritization – Managing multiple ad-hoc analytical requests from different departments while maintaining progress on long-term projects.
• Handling Ambiguity – Navigating situations where business requirements are unclear or data sources are fragmented.

Example questions or scenarios:

• "Describe a situation where your analysis led to a significant change in a product or business strategy. How did you convince stakeholders to take action?"
• "How do you handle a scenario where a product manager asks you to pull data to support a pre-determined conclusion that your initial analysis does not support?"

As a Data Analyst at Tipalti, your day-to-day responsibilities will revolve around turning raw transactional and product data into strategic assets. You will be responsible for defining, tracking, and analyzing key performance indicators (KPIs) that measure the health of Tipalti's core payment products.

You will collaborate closely with Product Managers to understand user behavior on both the Marketplace Portal (MP) and Accounts Payable (AP) platforms. By analyzing clickstream data, feature adoption rates, and user drop-off funnels, you will help identify areas where the user experience can be streamlined to increase customer satisfaction and platform retention.

In addition to product analytics, you will support operations and risk teams by monitoring transaction flows, identifying patterns of payment failures, and analyzing fraud detection metrics. Your reports and dashboards will enable these teams to proactively address issues, ensuring that global payment processing remains fast, secure, and compliant with international regulations.