At United Airlines, data is the engine that drives operational excellence, customer satisfaction, and strategic growth. As a Data Analyst, you will sit at the intersection of business strategy and technical execution, transforming massive, complex datasets into actionable insights. United Airlines operates thousands of flights daily across a global network, generating vast amounts of data from flight operations, customer bookings, loyalty programs, and aircraft maintenance. Your role is critical in translating this data into smarter, faster business decisions.

You will contribute to solving highly complex, real-world problems that directly impact the airline's bottom line and customer experience. Whether you are optimizing flight schedules, analyzing fuel efficiency, predicting passenger demand, or improving the efficiency of baggage handling systems, your work has a tangible impact. You will work closely with cross-functional partners in operations, network planning, revenue management, and digital technology to build data pipelines, design interactive dashboards, and deliver predictive models.

This role requires a unique blend of technical expertise, business acumen, and communication skills. United Airlines looks for analysts who are not just technically proficient in querying and manipulating data, but who are also curious problem-solvers. You must be able to look beyond the numbers to understand the underlying operational realities of a global airline, making this one of the most dynamic and rewarding data roles in the aviation industry.

The questions you will face during the United Airlines hiring process are designed to evaluate your technical execution, business intuition, and behavioral alignment with the company’s core values. These questions are drawn from real reported interview experiences and are structured to test your practical problem-solving abilities rather than rote memorization.

SQL and Database Querying

SQL is heavily tested throughout the technical rounds. You will need to demonstrate a strong command of relational databases and the ability to write clean, optimized queries under pressure.

• Write a query to find the second-highest salary from an employee table using a subquery and then rewrite it using a window function.
• Explain the difference between a LEFT JOIN, RIGHT JOIN, INNER JOIN, and FULL OUTER JOIN using an airline passenger database scenario.

Preparing for an interview at United Airlines requires a balanced approach that covers technical mastery, structured problem-solving, and cultural alignment. Interviewers want to see how you think, how you handle ambiguity, and how you communicate your findings to non-technical stakeholders.

Technical Mastery – You must be highly proficient in SQL and either Python or advanced Excel (including VBA). Review core database concepts, write clean queries on the fly, and be prepared to explain the computational efficiency of your code. Practice writing SQL queries on a whiteboard or shared screen without the aid of auto-complete.

Structured Problem Solving – When faced with case studies or guesstimates, the final number is less important than the framework you use to get there. Clearly state your assumptions, break the problem down into logical components, and sanity-check your final answer. Always tie your analytical approach back to airline operations and business outcomes.

Collaborative Communication – Data analysts at United Airlines do not work in a vacuum. You will need to explain complex analytical concepts to operational managers and business executives. Practice translating technical findings into clear, high-level business recommendations, and demonstrate how you build consensus across cross-functional teams.

Operational Resiliency – The airline industry is fast-paced and highly susceptible to external disruptions like weather, air traffic control, and mechanical issues. Show that you can think on your feet, adapt to rapidly changing requirements, and remain calm under pressure.

The interview process for a Data Analyst at United Airlines typically spans three to four rounds, depending on whether you apply through university recruitment, a direct referral, or a general job posting. The process is designed to evaluate both your technical execution and your strategic problem-solving capabilities.

For most candidates, the journey begins with a resume screening followed by an online technical assessment. This assessment typically evaluates your coding skills (primarily SQL and Python), logical reasoning, and basic computer science concepts. If you are referred by an internal employee, you may bypass this initial assessment and proceed directly to the technical interviews.

Following the initial screening, you will participate in one or two technical rounds. These interviews focus heavily on live coding, database querying, and your familiarity with analytical tools like Excel, VBA, and data visualization platforms. You will also face a dedicated business case study and guesstimate round, which is often cited by candidates as the most critical hurdle in the process. The final round typically consists of a behavioral and HR interview to assess your communication style, project experience, and cultural fit within the airline.

The timeline above outlines the standard progression from your initial application to the final offer. Candidates should expect a rigorous evaluation at each stage, with the technical and case study rounds serving as major eliminators. It is highly recommended to manage your preparation schedule to ensure you are fully polished by the time you reach the intensive case study and project discussion phases.

To succeed in the United Airlines interview process, you must understand exactly what is being evaluated in each core area and how to demonstrate your expertise.

SQL & Database Querying

SQL is the foundational tool for data extraction at the airline. Interviewers will assess your ability to manipulate complex relational databases to extract operational insights.

Be ready to go over:

• Complex Joins – Understanding when to use outer joins versus inner joins, and how to join multiple tables without creating Cartesian products.
• Window Functions – Utilizing ROW_NUMBER(), RANK(), DENSE_RANK(), LEAD, and LAG to perform analytical calculations across rows.
• Aggregations and Grouping – Using GROUP BY, HAVING, and nested subqueries to summarize operational data like flight delays or passenger counts.
• Advanced concepts (less common) – Query optimization strategies, indexing, and writing recursive CTEs for hierarchical data structures.

Example questions or scenarios:

• Write a query to find the top three airports with the highest average departure delay times, excluding airports with fewer than 50 daily departures.
• Calculate the month-over-month growth rate of MileagePlus sign-ups using window functions.

Python & Analytical Libraries

Python is used for advanced data manipulation, statistical analysis, and automating data pipelines. Interviewers want to see clean, readable, and efficient code.

Be ready to go over:

• Pandas DataFrames – Merging, filtering, grouping, and handling missing data within large datasets.
• NumPy Operations – Performing vectorized operations and working with multi-dimensional arrays efficiently.
• Data Visualization – Creating clear, informative plots using libraries like Matplotlib or Seaborn to communicate data trends.
• Advanced concepts (less common) – Writing object-oriented Python code (classes) and building basic predictive models using Scikit-Learn.

Example questions or scenarios:

• Write a Python function to clean a raw dataset of flight telemetry data, replacing missing altitude values with the median value of that specific flight path.
• Create a visualization script that displays the distribution of baggage processing times across different terminals.

Business Case Studies & Guesstimates

This area evaluates your business intuition and structured thinking. You must demonstrate that you can translate a vague business problem into a structured analytical framework.

Be ready to go over:

• Operational Guesstimates – Breaking down large, ambiguous estimation problems using logical assumptions and mental math.
• Root Cause Analysis – Systematically investigating a sudden shift in business metrics (e.g., a sudden increase in lost baggage at a specific hub).
• Cost-Benefit Analysis – Evaluating the financial trade-offs of operational decisions, such as upgrading gate technology versus hiring more ground staff.

Example questions or scenarios:

• Walk us through how you would estimate the number of active flight attendants currently in the air over North America.
• A key domestic route is showing a decline in profitability despite high passenger volumes. How would you analyze the data to find the cause?

Behavioral & Team Fit

United Airlines values collaboration, customer focus, and adaptability. Your behavioral interviews will assess how you handle conflict, manage stakeholders, and align with the company's operational values.

Be ready to go over:

• Conflict Resolution – How you handle disagreements with stakeholders or team members regarding data interpretations or project priorities.
• Managing Ambiguity – Examples of when you had to deliver an analysis with incomplete or messy data.
• Impact Communication – How you successfully communicated complex data findings to a non-technical audience to drive a business decision.

Example questions or scenarios:

• Describe a time when you discovered an error in your analysis after presenting it to a stakeholder. How did you handle it?
• Tell me about a highly ambiguous project you worked on and how you structured your approach to deliver results.

As a Data Analyst at United Airlines, your day-to-day responsibilities will vary depending on your specific team (e.g., Network Planning, Revenue Management, Customer Experience, or Flight Operations), but the core focus remains consistent: leveraging data to optimize airline performance.

You will be responsible for designing, building, and maintaining automated dashboards and reports that provide key performance indicators (KPIs) to leadership. This involves writing robust SQL queries to extract data from data warehouses and utilizing visualization tools to make that data easily digestible. You will act as the bridge between raw data and business action, ensuring that operational teams have the insights they need to make real-time decisions.

Collaboration is a major component of this role. You will work closely with data engineers to ensure that data pipelines are reliable and optimized, and with business stakeholders to understand their analytical needs. Additionally, you will conduct ad-hoc analyses to investigate operational anomalies, evaluate the success of new business initiatives, and build predictive models to forecast demand, fuel consumption, or passenger behavior.