Comcast Data Analyst interview typically runs 3 rounds: screening, Tableau, SQL. It usually takes a few weeks and is uneven, with later rounds more role-relevant.
$81K
Avg. Base Comp
$97K
Avg. Total Comp
3
Typical Rounds
2-4 weeks
Process Length
Our candidates report that Comcast is looking for analysts who can connect the dots between tools and business context, not just recite syntax. In one experience, the early conversation felt generic and light on follow-up, but the later discussions quickly shifted into hands-on Tableau and SQL work. That pattern tells us the company is less interested in polished storytelling than in whether you can actually navigate data, explain your choices, and translate results into something useful for the business.
A recurring theme is that Comcast seems to value practical fluency over deep theory. The SQL questions were described as basic to intermediate, but they weren’t purely technical; they also tested how the candidate would apply analysis to real scenarios. That’s an important signal for this role: we’ve seen that candidates do best when they can show they understand the why behind a query or dashboard decision, not just the mechanics. The bar appears to be centered on clear analytical judgment and comfort with common reporting tools.
We also noticed that the process can feel uneven at first, which means first impressions may not fully reflect the eventual evaluation. One candidate said the initial interviewer seemed disengaged, yet the later rounds were much more relevant and ultimately led to an offer. For us, that suggests Comcast may use the earlier conversation as a broad filter, but the real decision hinges on whether you can handle the day-to-day realities of the role: practical analysis, business-aware interpretation, and solid Tableau/SQL execution.
Synthetized from 1 candidates reports by our editorial team.
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Featured question at Comcast
Find the missing integer from a array of consequtive integers
| Question | |
|---|---|
| Address Schema | |
| Hurdles In Data Projects | |
| Improve Search Results | |
| Why Do You Want to Work With Us | |
| Your Strengths and Weaknesses | |
| 2nd Highest Salary | |
| Top Three Salaries | |
| Rolling Bank Transactions | |
| Prime to N | |
| Compute Deviation | |
| Button AB Test | |
| P-value to a Layman | |
| Paired Products | |
| Size of Joins | |
| Over-Budget Projects | |
| Raining in Seattle | |
| Top 3 Users | |
| Bagging vs Boosting | |
| Decreasing Comments | |
| Google Maps Improvement | |
| Bank Fraud Model | |
| Closed Accounts | |
| Identifying User Sessions | |
| Liked Pages | |
| Digital Library Borrowing Metrics | |
| Sort Strings | |
| Revenue Retention | |
| Group Success | |
| Significance Time Series |
Synthesized from candidate reports. Individual experiences may vary.
An initial screening conversation that felt fairly routine and generic. The interviewer asked a standard behavioral question about handling a challenge at work, but there was little follow-up and limited digging into the candidate’s background.
A more role-relevant interview focused on practical Tableau and SQL fundamentals. The discussion included basic to intermediate questions and required the candidate to explain their thinking clearly.
A second technical interview centered entirely on SQL. Beyond syntax, the questions tested business understanding and how the candidate would apply analysis to real-world problems.