What is a Data Analyst at Comrise?

As a Data Analyst at Comrise, you are the critical bridge between raw information and strategic business decisions. Comrise relies on precise, timely, and actionable data to drive operations, optimize client delivery, and refine internal processes. In this role, you do not just pull numbers; you transform complex, fragmented datasets into clear narratives that empower leadership and operational teams to act with confidence.

Your impact will be felt across multiple dimensions of the business. Whether you are streamlining reporting workflows, building dynamic dashboards, or uncovering inefficiencies in global operations, your work directly influences how Comrise scales. Given the specific focus on Power Query for this position, you will be tackling deep data transformation challenges, ensuring that the foundational data models supporting our reporting infrastructure are robust, automated, and highly accurate.

Expect an environment that balances high-scale technical challenges with strategic business exposure. You will collaborate closely with cross-functional teams—from engineering to business operations—often working with stakeholders in key regional hubs like Taguig and beyond. This role is designed for analytical thinkers who thrive on untangling messy data and take pride in architecting elegant, automated solutions that save time and drive revenue.

Getting Ready for Your Interviews

Thorough preparation is the key to navigating the Comrise interview process with confidence. We evaluate candidates not just on their technical syntax, but on their ability to apply those skills to real-world business ambiguities.

Focus your preparation on these key evaluation criteria:

• Technical Proficiency – You must demonstrate deep expertise in data transformation tools, specifically Power Query (including M code), SQL, and advanced Excel. Interviewers will look for your ability to efficiently clean, merge, and structure large datasets.
• Analytical Problem-Solving – This measures how you approach unstructured problems. We evaluate your ability to break down a vague business request, identify the necessary data sources, and design a logical path to the solution.
• Business Acumen & Storytelling – Data is only as valuable as the insights it generates. You will be assessed on your ability to translate complex technical findings into clear, actionable recommendations for non-technical stakeholders.
• Adaptability & Collaboration – Comrise values proactive communicators who can navigate shifting priorities. Interviewers will look for evidence of how you work within cross-functional teams, manage stakeholder expectations, and adapt to new tools or methodologies.

Interview Process Overview

The interview journey for a Data Analyst at Comrise is designed to be rigorous but highly collaborative. We want to see how you think, how you code, and how you communicate. The process typically begins with an initial recruiter screen focusing on your background, alignment with the role, and high-level technical familiarity.

If you progress, you will face a dedicated technical assessment phase. Because this role heavily emphasizes Power Query and data transformation, candidates often encounter a practical take-home assignment or a live technical screening. This is your opportunity to showcase your hands-on ability to ingest, clean, and model messy data under realistic constraints. We care deeply about the efficiency of your queries and the logic behind your data modeling choices.

The final stages consist of deep-dive interviews with the hiring manager and key team members. These rounds blend technical deep-dives with behavioral and scenario-based questions. The focus here shifts slightly from pure execution to strategy, stakeholder management, and cultural alignment. You should expect a fast-paced but conversational environment where interviewers are genuinely interested in your problem-solving framework.

This visual timeline outlines the typical progression from your initial application through the technical and behavioral stages to the final offer. Use this to pace your preparation, ensuring your technical skills are sharp for the middle stages while reserving time to refine your business narratives and behavioral examples for the final rounds. Note that specific timelines may vary slightly depending on team availability and regional nuances in the Taguig office.

Deep Dive into Evaluation Areas

To succeed, you need to deeply understand the core competencies our interviewers are assessing. Below are the major evaluation areas you will encounter.

Data Transformation and Power Query

This is the technical heartbeat of the role. Interviewers need to know that you can handle complex data wrangling without relying on inefficient manual processes. Strong performance here means demonstrating a mastery of Power Query Editor, an understanding of M formula language, and the ability to optimize queries for performance.

Be ready to go over:

• Query Optimization – Techniques for reducing load times, minimizing API calls, and avoiding common bottlenecks like the "Formula.Firewall" error.
• Advanced Data Shaping – Pivoting, unpivoting, grouping, and merging multiple disparate data sources efficiently.
• M Code Fundamentals – Moving beyond the GUI to write or edit custom M code for complex conditional logic or dynamic data ingestion.
• Advanced concepts (less common) – Creating custom functions in Power Query, incremental refresh strategies, and handling complex JSON/XML parsing.

Example questions or scenarios:

• "Walk me through how you would optimize a Power Query that is currently taking too long to load due to multiple heavy merges."
• "Explain a time you had to write custom M code because the standard Power Query UI could not handle the transformation requirement."
• "How do you handle dynamic column names when unpivoting data from a source that changes monthly?"

SQL and Relational Databases

While Power Query is vital, SQL remains the foundational language for data extraction. You will be evaluated on your ability to write clean, efficient, and accurate queries to pull data from relational databases before it even reaches your BI tools.

Be ready to go over:

• Complex Joins and Subqueries – Knowing when to use different types of joins and how to structure nested queries.
• Window Functions – Using functions like ROW_NUMBER(), RANK(), and LEAD()/LAG() to perform advanced analytical calculations.
• Data Aggregation – Grouping data effectively and using conditional aggregations (e.g., CASE WHEN within SUM).
• Advanced concepts (less common) – Query execution plans, index optimization, and database schema design.

Example questions or scenarios:

• "Write a query to find the top 3 highest-billing clients per region over the last quarter."
• "Explain the difference between a CTE (Common Table Expression) and a temporary table, and when you would use each."
• "How would you troubleshoot a SQL query that is returning duplicate rows after a series of left joins?"

Business Logic and Dashboard Design

Data must drive action. This area tests your ability to take a cleaned dataset and present it in a way that makes sense to business leaders. Strong candidates do not just build charts; they build intuitive, automated reporting solutions.

Be ready to go over:

• Metrics Definition – Translating vague business goals into trackable KPIs.
• Visual Best Practices – Choosing the right chart types and designing dashboards that guide the user's eye to the most critical insights.
• DAX (Data Analysis Expressions) – If using Power BI alongside Power Query, your ability to write complex measures for time-intelligence and dynamic filtering.
• Advanced concepts (less common) – Row-level security (RLS) implementation and automated alert configurations.

Example questions or scenarios:

• "A stakeholder asks for a dashboard to track 'team productivity.' How do you define that metric and what visuals do you choose?"
• "Describe a time when your data contradicted a business leader's assumption. How did you present your findings?"
• "Walk me through your process for validating the accuracy of a newly built dashboard before releasing it to production."

Key Responsibilities

As a Data Analyst at Comrise, your day-to-day work will be highly dynamic, balancing immediate reporting needs with long-term data infrastructure improvements. Your primary responsibility will be designing and maintaining robust data pipelines using Power Query, ensuring that data flowing from various internal systems and client platforms is clean, structured, and ready for analysis.

You will spend a significant portion of your time collaborating directly with operations managers, finance teams, and leadership. This involves translating their strategic questions into technical requirements, executing the data extraction, and delivering automated dashboards or reports. You are expected to be proactive—identifying anomalies in the data, investigating root causes, and proposing process improvements to prevent future data quality issues.

Additionally, you will drive initiatives to modernize legacy reporting. Many projects will require you to audit existing Excel-heavy workflows, untangle complex manual formulas, and rebuild them into streamlined, automated Power Query and SQL processes. You are not just maintaining the status quo; you are actively engineering a more efficient data culture within the company.

Role Requirements & Qualifications

To be highly competitive for the Data Analyst role at Comrise, candidates must present a strong blend of technical execution and business communication skills.

• Must-have skills – Expert-level proficiency in Power Query (including M code) and advanced Excel. Strong command of SQL for database querying. A proven track record of translating business requirements into technical data models. Excellent verbal and written communication skills to manage stakeholder relationships.
• Experience level – Typically, candidates need 3+ years of dedicated experience in data analysis, BI development, or a similar data-centric role. Experience dealing with messy, unstructured data from diverse sources is critical.
• Soft skills – High autonomy and problem-solving resilience. You must be comfortable navigating ambiguity and managing multiple reporting requests simultaneously without losing attention to detail.
• Nice-to-have skills – Proficiency in Power BI and DAX. Experience with Python or R for advanced statistical analysis. Familiarity with the staffing, consulting, or HR tech industry domains.

Common Interview Questions

The questions below represent the patterns and themes frequently encountered by candidates interviewing for data roles at Comrise. While you may not be asked these exact questions, practicing them will help you build the mental muscle memory needed to articulate your thought process clearly. Do not memorize answers; instead, focus on structuring your responses logically.

Power Query & Data Transformation

These questions test your hands-on experience with the specific tools required for the role. Interviewers want to see that you understand the nuances of data shaping.

• How do you handle errors in Power Query without causing the entire dataset load to fail?
• Walk me through the steps to dynamically combine multiple Excel files from a single SharePoint folder using Power Query.
• Explain a scenario where you would use a Left Anti Join in Power Query.
• What is the difference between Table.Buffer and List.Buffer, and when would you use them in M code?
• How do you optimize a Power Query model to ensure the fastest possible refresh times?

SQL & Technical Logic

Expect practical, scenario-based questions that test your ability to manipulate relational data efficiently.

• Write a SQL query to calculate the month-over-month growth rate of active users.
• Explain the difference between RANK(), DENSE_RANK(), and ROW_NUMBER(). Give an example of when you would use each.
• How do you identify and remove duplicate records in a SQL database?
• Describe a time you had to optimize a slow-running SQL query. What steps did you take?
• What are the differences between a WHERE clause and a HAVING clause?

Behavioral & Stakeholder Management

These questions evaluate your cultural fit, leadership potential, and how you handle the realities of a fast-paced business environment.

• Tell me about a time you had to explain a complex technical data issue to a non-technical stakeholder.
• Describe a situation where you received conflicting data requests from two different managers. How did you prioritize?
• Tell me about a project where the initial data provided was completely unusable. How did you salvage the situation?
• How do you ensure the accuracy and integrity of your reports before delivering them to leadership?
• Describe a time you proactively identified a business problem through data that nobody else had noticed.

Frequently Asked Questions

Q: How technical is the interview process for the Data Analyst role at Comrise? The process is highly technical, particularly regarding Power Query and SQL. You should expect to prove your practical abilities through a technical assessment or live case study. However, the technical rigor is always balanced with questions about business application and stakeholder communication.

Q: How much time should I spend preparing for the technical assessment? Candidates typically spend 5 to 10 hours reviewing advanced Power Query transformations, M code basics, and complex SQL joins. Focus your prep on real-world scenarios, like cleaning messy survey data or merging mismatched financial records, rather than just textbook definitions.

Q: What differentiates an average candidate from a great candidate? An average candidate can write the code to pull the data. A great candidate asks why the data is being pulled, anticipates the follow-up questions the business will have, and designs a scalable, automated solution that addresses the root business need.

Q: Is this role fully remote, hybrid, or onsite in Taguig? While specific arrangements can vary by team and current company policy, roles based in Taguig, NCR often operate on a hybrid model. Be prepared to discuss your ability to collaborate effectively across both in-person and distributed global teams.

Q: How long does the interview process typically take? From the initial recruiter screen to the final offer, the process generally takes between 3 to 5 weeks. Comrise moves efficiently, but the timeline can be influenced by the completion speed of the technical assessment and the availability of cross-functional interviewers.

Other General Tips

• Master the "Think Out Loud" Method: During live technical screens, your thought process is just as important as the final code. If you get stuck on a specific M code syntax or SQL function, explain what you are trying to achieve. Interviewers will often guide you if your logic is sound.
• Contextualize Your Impact: When answering behavioral questions, always use the STAR method (Situation, Task, Action, Result). Make sure to quantify your results. Did your Power Query automation save the team 10 hours a week? Did your dashboard uncover a $50k revenue leak? Numbers matter.

• Brush Up on Data Modeling: Knowing how to clean data is step one; knowing how to structure it into a star schema for efficient reporting is step two. Be prepared to discuss fact tables, dimension tables, and primary/foreign key relationships.
• Acknowledge Edge Cases: When designing a solution during a case study, explicitly mention how you would handle null values, unexpected data types, or missing dates. Showing that you anticipate data anomalies proves you have real-world experience.

Summary & Next Steps

Securing a Data Analyst position at Comrise is an exciting opportunity to place yourself at the center of business-critical operations. By stepping into this role, you will be empowered to shape how the organization views and utilizes its data, driving efficiencies that have a tangible impact on the bottom line. The emphasis on Power Query and advanced data transformation means your technical skills will be continually challenged and refined.

To succeed, focus your final preparation on marrying your technical execution with strong business storytelling. Review your most complex data wrangling projects, practice articulating your SQL and M code logic out loud, and prepare concrete examples of how you have managed stakeholder expectations. Remember that interviewers are looking for a collaborative problem-solver, not just a human calculator.

This compensation data provides a baseline expectation for data-focused roles within the region. Use this information to understand the market rate, keeping in mind that actual offers will vary based on your specific depth of experience with Power Query, your performance during the technical assessments, and your overall alignment with the role's strategic demands.

You have the analytical mindset and the technical foundation required to excel. Approach these interviews with confidence, curiosity, and a readiness to showcase the real-world value you can bring to Comrise. For more insights, peer experiences, and targeted practice scenarios, continue exploring resources on Dataford. Good luck—you are ready for this!