FAANG Data Engineer Interview Questions
FAANG Data Engineer Interview Questions
FAANG-tagged data engineer interview questions with per-company rubrics.
FAANG data engineer interview questions tagged from reported Meta, Amazon, Google, Netflix, and Apple loops. Each company's rubric is different. Meta weights communication. Amazon weights Leadership Principles. Google weights complexity reasoning. Netflix weights Spark. Apple weights warehouse architecture. The catalog is filterable down to a single company once you know your target.
FAANG (Meta, Amazon, Apple, Netflix, Google) data engineer interview loops share a common high-level structure (SQL, Python, data modeling, system design, behavioral) but the rubric weights and the specific focus areas differ significantly per company. A data engineer candidate who optimizes for one FAANG without understanding the others' specific bars often clears one loop and fails the next.
Meta (formerly Facebook) weights communication and trade-off articulation heavily. The SQL round tilts toward window functions and gap-and-island patterns for engagement streak detection. Presto and Trino dialect is what you see internally. Design rounds frequently center on the ads attribution pipeline (impressions, clicks, conversions with 28-day windows, multi-touch attribution) or the feed-ranking signals pipeline (10B+ events per day, single-digit-millisecond serving latency for the ML ranker). The behavioral round at Meta explicitly scores 'thinks out loud' and 'asks clarifying questions' as separate dimensions from technical correctness.
Amazon weights correctness and clean code heavily in the technical rounds, with Leadership Principles framing every behavioral and design answer. The stack is AWS-native: Redshift, Glue, EMR, Kinesis, S3, Athena. The bar-raiser round (an outside interviewer whose vote can veto a hire) is unique to Amazon and probes deeper on cultural fit. The data engineer SQL round covers Redshift-specific dialect (DISTKEY, SORTKEY, COPY, VACUUM).
Google weights complexity reasoning in the Python round more than other data engineer loops; Big-O articulation expected for every data structure choice. The stack is GCP-native: BigQuery, Dataflow, Pub/Sub, Dataproc. BigQuery's QUALIFY and ARRAY/STRUCT manipulation come up in the SQL round. Design rounds expect a GCP-native architecture with cost reasoning (BigQuery slot consumption, Dataflow worker hours).
Netflix runs Spark at extreme scale; the PySpark or Scala-Spark round is dedicated (45-60 minutes) and the SQL round includes Spark SQL questions. Iceberg as the table format is internal default; mention it in design rounds. Late-arriving data is a recurring theme; clients can be offline for days and events need to update past aggregates without overwriting.
Apple's data engineer interview loop varies more by team than the other FAANGs. The services and analytics teams tilt toward warehouse architecture (currently a mix of Hadoop/Hive legacy and modern Snowflake/Spark). The hardware teams tilt toward operational pipelines feeding manufacturing analytics. The bar is consistently high but the topics covered shift by team.
- How do FAANG data engineer loops differ from each other?
- Shared high-level structure (5 rounds: SQL, Python, modeling, design, behavioral) but different rubric weights. Meta weights communication. Amazon weights Leadership Principles and correctness. Google weights complexity reasoning in Python. Netflix weights Spark and late-arriving-data design. Apple varies by team. The dialect and stack assumed in interviews also differs per company.
- Should I prep for all 5 FAANG at once or one at a time?
- One at a time once you know your target. The foundational skills (SQL, Python, modeling) are 80 percent overlap; the per-company specifics (Presto syntax for Meta, BigQuery for Google, Leadership Principles for Amazon, Iceberg for Netflix) are the last-mile 20 percent that makes the difference between a strong loop and a no-hire. If you are early in prep, build the foundation; if you are 2-4 weeks from an onsite, focus on the specific company's bar.
- Which FAANG has the highest data engineer bar?
- Subjective and varies by team. Common takes: Netflix has the highest bar for Spark and large-scale design; Google has the highest bar for Python complexity reasoning; Meta has the highest bar for narration and communication; Amazon has the highest bar for cultural fit (via Leadership Principles and the bar-raiser round); Apple varies most by team. None is easy; all expect a candidate who can clear all 5 rounds.
- What is the FAANG-versus-non-FAANG difference for data engineer interviews?
- FAANG loops are typically more rigorous on scale (problems framed at 10B+ events per day, multi-region complexity), more rigorous on edge cases (multi-seed-grader-style fishing for NULL bugs, tie handling, idempotency), and more rigorous on behavioral rounds (specific cultural frameworks at Meta and Amazon, conversational depth at Netflix). Non-FAANG loops at strong companies (Stripe, Databricks, Snowflake, Airbnb, Uber) often have comparable technical bars but different cultural framings.
- What stack should I assume in data engineer design rounds at each FAANG?
- Meta: Presto/Trino plus Hive plus Spark plus internal tools. Amazon: AWS-native (Kinesis, Glue, EMR, S3, Athena, Redshift, DynamoDB). Google: GCP-native (Pub/Sub, Dataflow, BigQuery, Dataproc, Cloud Storage, Bigtable). Netflix: Spark plus Iceberg plus Mantis plus Kafka plus S3. Apple: varies by team; Snowflake and Spark common in newer teams, Hadoop/Hive legacy in older ones.
- How do I handle the cultural fit rounds at FAANG?
- Amazon: 5-7 STAR-D stories explicitly mapped to 2-3 Leadership Principles each. Meta: emphasis on communication and asking clarifying questions; less rigid framework. Google: Googleyness and Leadership themes (ownership, collaboration, ambiguity tolerance) without rigid framework. Netflix: 'stunning colleagues' bar; expect probing for ownership and the ability to disagree productively. Apple: varies; generally expect direct, technical, no-fluff answers.
- What level should I target if I have 5 years of experience as a data engineer?
- 5 years typically maps to L5/E5/Senior across FAANG. The L5 bar weights trade-off articulation, failure-mode naming (3 per component in design rounds), and mid-round adapt-on-fly. L4 (4-5 years floor) emphasizes clean foundational solutions; L6 (8-10+ years) emphasizes org-level design influence. Recruiters can sometimes flex you between L4 and L5 based on loop performance.
- What is the typical FAANG data engineer onsite duration?
- 4-5 hours for an onsite, 5-6 hours for senior+. 4-5 rounds of 45-60 minutes each, lunch interview (informal but observed), and sometimes a follow-up call for any unclear signals. Phone screen is typically 60-75 minutes covering SQL plus a behavioral or shortened design. Whole loop process: 4-8 weeks from first phone screen to offer, depending on company and team availability.
346 practice problems matching this filter. Domains: SQL (256), Python (76), Data Modeling (12), Pipeline Architecture (2). Difficulty: medium (146), easy (138), hard (62).
SQL (256)
- 10 Lowest Uptime Services - medium - Ten services at the bottom of the reliability chart.
- 30-Day Page View Counts - easy - Thirty days of engagement. Quick snapshot.
- 7-Day Token Retention - medium - Premium tokens, day by day.
- Above the Fold - hard - Every click is a vote on the ranking. Score each search.
- Active Users With April Transactions - easy - Active accounts that also opened their wallets. How many?
- After the Cutoff - easy - The calendar turned but prod kept moving. See which services never stopped shipping.
- All Infra Regions - easy - The infrastructure spans the globe. Map it.
- API Call Distribution Fraction - hard - Not all endpoints are created equal.
- Average Review Comments by Author - medium - Some authors get more feedback than others.
- Average Session Duration - medium - How long do users actually stay?
- Average Session Duration by Device - easy - Session length, device by device.
- Average Sessions Per User - hard - How often do users come back?
- Behavioral Range - easy - Power users don't just visit more. They do more things.
- Between the Spaces - medium - Every pause between words is a vote for length. Count them.
- Between Two Extremes - medium - Ignore the loudest and the quietest. The truth lives in the middle.
- Bookends of the Week - hard - Every week has two edges. Weigh what lands on each.
- Both Arms of the Trial - easy - Some features were tried both ways.
- Build Success Rate by Trigger - medium - Which triggers produce green builds?
- Build Success vs Failure by Repo - medium - Green versus red, repo by repo.
- Busy Authors - medium - Some developers spread their commits everywhere.
- Campaign Click Rate - medium - Among engaged users, which campaigns landed.
- Campaign Revenue Totals - easy - Every campaign has a price tag. Total them up.
- CDN-Related DNS Lookups - easy - DNS lookups tied to the CDN.
- Character Position in Endpoint - easy - URL patterns, character by character.
- Cheapest CDN Route - easy - The cheapest path across regions.
- Cheapest Cost Per Region - easy - Lowest spend per region.
- Cheapest Transaction per User - easy - Everyone has a smallest purchase.
- Clean Exit - easy - Priority one. Only some of them made it to the end.
- Clicked Ad Impressions - easy - They saw the ad. They clicked.
- Cloud Cost Trend Analysis - medium - Cost trends across billing periods.
- Competing Standards - hard - Every framework has a star model.
- Content Session Counts - medium - Session metrics, content item by item.
- Cost Share Within Category - medium - Each entry's slice of the category total.
- Creatures of Habit - hard - Every big team has one service it can't quit.
- Customer Full Name Concat - easy - First name, last name. Combine them.
- Custom Message Type Counts - medium - Not all messages are created equal.
- Daily Cross-Platform Users - easy - Mobile and web. Same day, same users?
- Daily Error Resolution Ratio - medium - Reported versus removed. The daily ratio.
- Daily Net Revenue - hard - Net revenue, day by day. Refunds included.
- Daily Session and User Counts - medium - Sessions and users, day by day.
- Days with More Edited Than Unedited Messages - medium - Some days, more messages get edited than sent.
- Deep Pockets - medium - One month, every customer, every dollar accounted for.
- Deployments per Environment - medium - Dev, staging, prod. Where do most deploys land?
- Device Type Serving Most Users - medium - One device type serves more users than the rest.
- Did Anyone Actually Read It? - easy - A push isn't a win until a thumb taps it.
- Diminishing Returns - medium - When search comes back thin, does the click still follow?
- Disabled-Flag Share by Owner - medium - Which teams ship everything off by default.
- Distinct Product Categories - easy - A quick category inventory.
- Double Take - medium - Passed QA twice. That's the problem.
- Double Vision - easy - Before the records move, the ones wearing the same name twice have to surface.
- Duplicated User Event Messages - medium - Duplicated messages from the alerts topic.
- Ebb and Flow - hard - The rise and fall of revenue, one month against the last.
- Echo Chamber - medium - Same status, same pattern. Coincidence?
- Engagement Gap - medium - Zero transactions is still a data point. Count everyone.
- Errors With Service Health - easy - Error data, enriched with health context.
- Even-ID February Signups - easy - A very specific slice of a very specific cohort.
- Even-ID June Signups - easy - Odd IDs, even IDs. The filter is precise.
- Event Count on Key Days - easy - Key days. Key event volumes.
- Events by Month Across Years - easy - Month by month, year by year. The pattern emerges.
- Event Types Spanning Multiple Months - easy - Some events span seasons.
- Fastest Page View to Click - hard - How fast from view to click?
- Fault Lines - medium - Errors by day and region. Some areas are worse than they appear.
- Feature Flag Adoption - medium - How widely adopted are the flags?
- Feature Flag Fan vs Detractor Pairs - hard - Some users love the flag. Others want it gone.
- Feature Name Intersection - hard - Training names versus serving names. The overlap.
- Filtered User Roster - easy - A clean roster for the all-hands.
- Find Deploy Authors - easy - Same person. Many different spellings.
- Find the Fifth Largest Cost - medium - Not the biggest. Not the smallest. The fifth.
- First Among Many - medium - Each segment has a favorite category.
- First Half of Page Views - medium - Half the data. The first half.
- First Impressions - easy - Just the first three characters. That is all.
- First Interaction Credit - hard - Attribute transactions to earliest touchpoint
- First Migration Record - easy - The very first migration. Where it all began.
- Frequent Message Senders - medium - Someone is sending too many messages.
- Full Funnel - hard - Search. Browse. Buy. Only a few do all three.
- Gone to Ground - medium - The control group held steady. Some of them slipped away. Find the ones who stopped answering.
- Health Checks per Service - easy - Some services get checked constantly.
- Heavy Hitters - medium - Some repos never sleep.
- Heavy Namespaces - medium - Kubernetes has favorites. Some namespaces carry more weight.
- High Engagement Pages - hard - Some pages hold attention longer than others.
- Highest and Lowest Cloud Costs - medium - The extremes in cloud spending.
- Highest Daily Spend - medium - Somewhere in that window, someone broke the spending record.
- High Price Products - easy - Everything above 100.
- High-Rated In-Stock Percentage - easy - Highly rated and in stock. A rare combo.
- Impressions by Search Keyword - hard - Campaign performance, keyword by keyword.
- Inactive Users in Date Range - medium - Ghost accounts. Active signup, zero sessions.
- Infant Mortality - hard - The youngest ones break first.
- In the Shadow of the Peak - medium - Every provider has a top-line cost. Find the one right behind it.
- iOS Sessions by Device Type - medium - iOS engagement, device by device.
- Keys That Never Die - medium - Some API keys have no expiry date at all. That should worry someone.
- Kings of the Calendar - hard - Every month has a winner.
- Largest Group - easy - One group towers above the rest.
- Largest Single Cloud Cost - medium - One line item. The biggest bill of all.
- Last Five Batch Jobs - easy - The last five. A quick tail check.
- Last Migration Record - easy - The most recent migration. Is it the last?
- Last Seen - easy - Everyone has a most recent session.
- Latest Version Per Service - easy - The latest version deployed. Each service.
- Left on Read - medium - Every campaign fights for the tap. Find the ones the field is leaving behind.
- Live Wire - medium - The last switch each team flipped.
- Longest Deploy With Full Identifier - easy - The longest deployment. Full ID.
- Long Searches Containing 'er' - easy - Long queries with 'er'. A pattern?
- Losing Altitude - hard - Two months apart, the same campaigns. Find the ones that slipped.
- Low-Volume Stream Topics - medium - Quiet topics in the stream.
- Loyalty's Double Tap - medium - When a nudge and a banner team up.
- Many Eyes - medium - Every codebase draws its own circle of watchers. Count who shows up.
- Max Value Per Location - easy - Every location has a peak.
- Mentorship User Pairs - medium - Pair them up. Mentor and mentee.
- Messages Containing Keyword - easy - Flagged terms in the messages.
- Messages From Specific Users - easy - Specific users. What did they say?
- Metric Range by Department - medium - Where each team's numbers sit, low to high.
- Mid-CPU Nodes - easy - Not the heaviest. Not the lightest. The middle.
- Mobile Event Counts - easy - Mobile engagement, device by device.
- Most Common Monday Outcome - medium - Mondays have a pattern.
- Most Efficient Region by Token Usage - hard - Some regions squeeze more out of every token.
- Multi-Host Regions by Node Type - medium - Some regions are quietly building empires.
- Mutual Channel Connections - medium - Two users. What channels do they share?
- Never-Ordered Products - easy - In the catalog. Never purchased.
- Nodes by Region and Type - medium - Broken down by region. Broken down by type.
- Noisiest Tables by DQ Failures - medium - The tables that fail the most checks.
- Non-Draft Content - easy - Everything except drafts.
- Once and Only Once - hard - Repeated readings are noise. The value seen a single time is the signal.
- Only Here - hard - Exclusive to one source. Missing from the other.
- Open Wounds - hard - Every service has one alarm that was never silenced. Find the one that has been screaming the longest.
- Parallel Traces - medium - Same experiment. Different variants. Who overlaps?
- Past the Threshold - medium - Somewhere after the third visit, a habit quietly forms. Find the ones who crossed over.
- Peak Company - hard - Every token lived among others. Find the moment the crowd was largest.
- Pipeline Completion Rate - medium - How far do users get through the flow?
- Point of Entry - hard - Everyone starts by looking. Count who came back to buy.
- Power Users - medium - Engagement separates tourists from regulars.
- Power Users by Session Activity - medium - More sessions. More time. The power users.
- Presence vs. Participation - medium - Being in the region and being active are two very different things.
- Priciest Item in Each Category - medium - The most expensive item per category.
- Prime Real Estate - easy - Not every screen earns the build. Find the ones that do.
- Product Name Letter Replace - easy - A quick text transform on product names.
- Proof of Presence - medium - Two-factor sent. How many confirmed?
- Q2 Search Volume - easy - Q2 search volume. The numbers.
- Recurring Error Types - easy - The same errors, recurring.
- Regional Sales Growth QoQ - hard - Quarter-over-quarter growth. Region by region.
- Repeat Buyers Across Halves - medium - First half buyer. Second half buyer. Same person.
- Repeat Purchase Window - medium - The retention squad is looking for repeat purchasers.
- Resolved vs Unresolved Alerts - hard - Resolved versus open. By severity.
- Retargeting Campaign Impressions - easy - Retargeting impressions. All of them.
- Returning Buyers - medium - They came back and bought again.
- Return on Patience - medium - The best answers cost the least time. Find the ones that pay off.
- Reviewer Performance Metrics - medium - Some reviewers are thorough. Others are fast.
- Reviews Per Reviewer - easy - The workload split across reviewers.
- Rolling Revenue Average - hard - Smooth out the revenue bumps. The trend matters more.
- Rooms in Common - hard - Two people, one channel, a connection you never counted.
- Search Terms Starting With G - easy - Queries starting with 'g'.
- Second Highest Cloud Cost - medium - The second biggest bill on record.
- Seen or Ignored - medium - A send is only half the story. Find where the taps actually land.
- Server With Most Errors - medium - One server stands out. Not in a good way.
- Service Roll Call - easy - The mesh is sprawling. Find out exactly how many services are actually running.
- Services at Median Uptime - medium - Exactly at the median. Not above, not below.
- Service Scorecard - hard - Deploys vs. alerts. One row per service tells the whole story.
- Services With Multi-Quarter Uptime - hard - Multi-quarter uptime streaks.
- Session Count Distribution - hard - How are sessions distributed among the newest users?
- Session-Fit Content - easy - Content that fits the session length.
- Session Overview - medium - Full engagement picture, even for the ones who never showed up.
- Session Page View Distance - hard - Page view distance per session.
- Sessions Per Device Type - easy - Sessions, device by device.
- Shared Category Purchasers - medium - They bought different things from the same aisle.
- Shared Endpoints - medium - Shared credentials across endpoints.
- Signups by Age Bucket Since April - easy - Recent signups by age.
- Six Degrees - hard - Every reply ties two names together. Find whose web reaches the furthest.
- Symmetric Reply Network - medium - Every reply is an edge. Draw it both ways.
- Tables With Many DQ Failures - medium - Some tables have never once passed QA.
- The A/B Verdict - medium - Variant A or Variant B. The conversion numbers pick the winner.
- The Apprentices Still in the Forge - easy - A model is not a model until it stops learning and starts earning.
- The Blast Radius - medium - A reliability scoreboard for deploy teams.
- The Blind Spot - medium - Pages they haven't discovered yet.
- The Compliance Order - easy - Token scopes need to be in the right sequence before the audit.
- The Crowded Hour - easy - Every device type has a moment when the room is fullest. Find it.
- The February Cohort - easy - One signup window. One cohort. Who joined the club?
- The Floor Price - medium - Before the negotiation, find what each provider really charges at its cheapest.
- The Gap Between Neighbors - hard - Same region, and still they disagree.
- The Heaviest Hitters - easy - A handful of impressions earn more than the rest combined. Bring them to the top.
- The Heavy Hitters - easy - Total sales tell the real story. Surface the products that carry the catalog.
- The Legacy Hunt - easy - Old data. Still matters.
- The Long Tail - medium - Averages hide the pain. The tail is where SLOs live.
- The Loudest Caller - easy - One account carries the traffic. Trace it back to everything it can touch.
- The Loudest Neighbor - hard - In every namespace, one pod does most of the eating.
- The Loudest Voices - medium - In every channel, a few names never stop scrolling.
- The Merit Circle - medium - Ten seats at the top, and the ratings decide who sits.
- The Named Transaction - easy - Transaction IDs are useless without context. Bring in the product names.
- Then and Now - hard - Accuracy used to be higher.
- The Ninety-Day Comeback - hard - Everyone shows up once. Who comes back before the quarter ends?
- The Notification Lifecycle - medium - Sent, opened, ignored. What happened after the alert went out?
- The Notification That Paid Off - hard - The message went out to thousands. A smaller number actually bit.
- The Ones Worth Paging - hard - Three levels wake someone up at night. Tally each one.
- The Opening Run - easy - Before the tuning, before the records. What the first pass carried home.
- The Open Question - medium - Push sent. How many opened?
- The Podium Finish - medium - Top two products per category.
- The Publishing Audit - easy - Published years ago. Still generating views?
- The Quiet Outlier - hard - Ignore what the traffic does all day. Find the spike that barely showed up.
- The Relentless Searchers - medium - Most users look once and leave. A few never stop looking.
- The Space Between - hard - The time between events is the tell.
- The Space Between Us - hard - Every viewer lives inside a world of campaigns. Measure how much two of those worlds are really one.
- The Standing Fleet - easy - Some hosts wear many hats. Count the machines, not the mentions.
- The Tag Order - hard - Tags arrived in chaos. The system needs them in line.
- The Tiebreaker - easy - One column wasn't enough. The second column settles it.
- The Token Census - easy - How many tokens are out there?
- The Upgrade Divide - medium - The install numbers don't match the hype.
- The Vanishing Rows - easy - Some records disappear when the tables meet. Figure out why.
- The Waiting Room - easy - Signed up. Never verified. Never came back.
- The Weight of Between - easy - Between the floor and the ceiling, the ledger keeps its quiet accounts. Sort what rests there.
- The Weight of the Cloud - medium - Not every dollar counts the same. Close the quarter.
- Third Highest Spender - medium - Bronze medal in spending.
- Third Largest Batch Job - easy - Bronze medal in the batch job rankings.
- Threads Excluding User - easy - Every thread they're not part of.
- Three Lowest Distinct Cloud Cost Amounts - easy - The three cheapest bills on record.
- Titles Ending With S - easy - Naming conventions. Specifically the plurals.
- Top 10 CPU-Heavy Nodes - medium - The ten hungriest nodes.
- Top Active Senders per Channel - medium - Top three messages per channel by replies.
- Top Alert Resolvers - medium - The engineers who resolve the most.
- Top API Caller - medium - One user triggered more API calls than anyone.
- Top Cost Entry per Team - medium - The single biggest bill per team.
- Top Framework by Deployments - hard - The framework most often deployed.
- Top Identified Event Types - medium - The top users by events, but only the identifiable ones.
- Top Metric Values - easy - The five highest numbers. No duplicates.
- Top Percentile API Tokens - hard - The most suspicious tokens.
- Top Services by Uptime - medium - Uptime is a competition. Which services never blink?
- Total Cost by Category - easy - Total spend per category.
- Total Hours Between Consecutive Events - hard - Hours between state changes.
- Total User Spend - easy - Each customer's total. Summarized.
- Transaction Overview - easy - The executive snapshot. Users, products, revenue.
- Transaction Share of User Spend - medium - Each transaction's share of the whole.
- Trim Endpoints Right - easy - Trailing whitespace. Clean it up.
- Trim Search Terms Left - easy - Leading whitespace. Clean it up.
- Twice Over - medium - Same model, trained twice.
- Two Names on the Ledger - easy - Two accounts. One ledger. Watch the spend stack up.
- Two-Way Street - medium - A conversation reads the same from either side.
- Unclicked Searches by Campaign - medium - Searched but never clicked.
- Under the Line - medium - Twice the average is the ceiling. Find the teams comfortably beneath it.
- Unique Reporters per Content - medium - How many people flagged each item?
- Unique Searchers - easy - How many users actually searched?
- Unique Stream Topics - easy - A clean inventory of streaming topics.
- US-East KV Store Entries - easy - KV store inventory. us-east-1.
- User 360 - hard - One row per user. Everything they did, or didn't do.
- User Devices - medium - Desktop, mobile, tablet. What does each user actually use?
- User Engagement Summary - medium - Sessions plus searches. The full engagement picture.
- User Sessions on Specific Days - easy - One user. Specific days. What happened?
- Users Per Device Type - easy - Users per device. The split.
- Users Who Clicked Ads - easy - Ad clickers and their account details.
- Users Without Sessions - medium - Account created. Never logged in.
- Users With Purchase Events - easy - At least one purchase. That changes everything.
- Verbose by Design - hard - Some paths say in six segments what others say in two.
- Verify Commit ID Uniqueness - easy - Duplicate commit IDs. Are there any?
- View Count Per Page - easy - Every page has visitors. Some just have more.
- Views by Content Type - medium - Count content views broken down by content type
- Weekly Build Status Report - hard - Every CI run, bucketed by week.
- Weekly Transaction Volume - easy - Weekly volume. The pulse.
- When They Opened - medium - Push after push goes out. Some months, people actually read them.
- Where the Money Sits - medium - Every team carries a cost, and some of it is what keeps the servers running.
- Where the Year Leans - medium - Some teams file early, some file late. See which way each one tips.
- Who's Looking - easy - Every search is a question someone needed answered. Count the people asking.
Python (76)
- Against the Grain - medium - Turn the grid on its side and let every column stand up as a row.
- All Told - easy - Every shift leaves a number behind. Total the fleet.
- Batch Records - medium - Too many at once. Break them into groups.
- Carrying Forward - medium - The total grows with every row.
- Closing Bell - medium - Every share you own, priced at today's close. Tally the gains.
- Column Range - easy - From minimum to maximum. What is the spread?
- Corner to Corner - medium - A grid pressed flat still remembers its corners.
- Dictionary Key Intersection - medium - Two dictionaries. What do they share?
- Downstream - hard - Nothing runs until what it needs has run.
- Down the Line - medium - Load has to keep moving. Pass it down the line.
- Even Filter - easy - Only the even ones survive.
- Everything That Repeats - easy - Say it once, then say how many times it stayed.
- Every Trace - medium - It is in there somewhere. Where exactly?
- Explode List - easy - One row holds many values. Unpack it.
- Greeting Formatter Class - easy - First impressions are formatted carefully.
- High Water - easy - Every reading remembers the highest that came before.
- High Water Mark - easy - Even below zero, one reading still stands above the rest.
- Moving Day - hard - Old schema in, new schema out.
- Null Counter - easy - How many holes in the data?
- Out of Nowhere - hard - Every stream has a rhythm. Find the readings that break it.
- Quality Gate - easy - Not everything passes inspection.
- Quantile Calculator - easy - Mark the boundary value at a given point.
- Round and Round They Go - medium - Each face waits its turn as the wheel comes back around.
- Single File - easy - However deep the nesting, every voice arrives in its own turn.
- Sort Descending - easy - Biggest first. No exceptions.
- Subarray Signal - medium - One stretch carries the strongest signal.
- The Deep Config - medium - Every setting has a path. Trace it down to the value.
- The Deep Dive - easy - A specific position in the unsorted pile.
- The Dependency Resolver - medium - Everything depends on everything.
- The Dominant Signal - easy - Hottest items in the transaction log. Ties included.
- The Email Ranker - medium - Some inboxes see more action.
- The Event Bucketer - easy - Logs slotted into buckets.
- The Firehose - medium - A stream arrives out of order. Roll it up, one time window at a time.
- The First of Their Kind - easy - When the same record arrives twice, only the first one survives.
- The Forward Fill - easy - Patch the gaps in a noisy sensor stream.
- The Gap Filler - easy - Fill the Nones with the last real value.
- The Generous Ones - medium - The generous ones are obvious.
- The Halftime Score - easy - Middle value of a dataset. No built-in shortcuts.
- The Horizon Scanner - medium - For each position, what is coming up ahead?
- The IP Validator - easy - Real and fake, mixed together.
- The Last Known Good - medium - When a column goes quiet, its last reading keeps standing.
- The Log Pulse - easy - Some lines repeat themselves.
- The Long Run - easy - Say it once, then say how many times it kept saying it.
- The Middle Ground - hard - The middle value keeps moving.
- The Mirror Index - easy - Every value remembers who pointed to it.
- The Nearest Value Mapper - medium - Close enough counts. Ties go low.
- The Numbered Chair - easy - A standing list. Position n holds one entry.
- The One-Way Street - easy - The longest stretch that never turns around.
- The Only Difference - easy - Two versions of the same line. Surface only what changed.
- The Original Keeper - easy - Clean up duplicate events without losing the timeline.
- The Output Peak - hard - One stretch outpaced all the others.
- The Quiet Drift - medium - Two versions of the same truth.
- The Repeat Review - medium - The echo came back.
- The Resume Sifter - medium - Pull what's useful. Skip what you know.
- The Running Total - easy - Each position holds the sum of everything before it.
- The Schedule Cleaner - medium - Overlapping sessions. One clean line.
- The Sequel Spotter - easy - Spot the sequels hiding in the catalog.
- The Shifting Standard - medium - A benchmark in motion.
- The Shortest Path Home - medium - Every leaf remembers the road it came from. Bring them all back on one line.
- The Shortlist - medium - In every field, only a few rise to the top. Keep them.
- The Social Graph - easy - Everyone knows someone.
- The Spin Doctor - medium - Ninety degrees, but which way?
- The Squeeze - easy - aaabbb gets old fast. Shrink it.
- The Streak Breaker - easy - It has a problem with repetition.
- The Stream Averager - easy - The answer moves with the data.
- The Stream Joiner - hard - Events don't wait for each other. This does.
- The String Shrinker - easy - Compress the string. Shorter wins.
- The Target Hunt - medium - Pairs that hit a target. Every one of them.
- The Throttle Ceiling - medium - Too many requests in too short a timeframe. Throttle it.
- The Throttle Wall - hard - Stop the abusers. Let the rest through.
- The Trade Signal - easy - Buy low, sell high. Identify the ideal moment.
- Transform Column - easy - Same data, new shape.
- Value Count - easy - How many of each? Count them.
- What Changed Overnight - medium - Schema from yesterday vs today. Something changed.
- What the Night Changed - hard - Two photographs of the same table, a day apart. Account for everything that moved.
- Where the Line Breaks - easy - Every batch has a last piece. Mark it right.
Data Modeling (12)
- A Number for the Seller - easy - They want a total. Give them the right schema first.
- Content Engagement Data Model - hard - Post published. Now measure everything that happens next.
- Food Truck Operations Data Model - medium - Mobile vendor, fixed menu, unpredictable locations.
- Marketplace Sales Warehouse - hard - No schema given. The interviewer is watching.
- The Churner Who Came Back - hard - They cancelled. They came back. The report has to tell both stories correctly.
- The Last Mile - medium - Order placed. Now track it to the door.
- The Plan That Changed Twice This Month - medium - Subscribers come, go, downgrade, and share. The schema has to keep up.
- The Sales Architecture - medium - Numbers are easy. Making them queryable at scale is the real job.
- The Shape of a Run - medium - Two log lines bracket every process. Pair them and the fleet's rhythm appears.
- The Transfer Request - medium - Apply, wait, get approved or denied. Track all of it.
- The Vanishing State - easy - A status column forgets the moment it changes. Model the schema that remembers.
- Two Wallets - medium - Two user types. Multiple payment methods. One messy billing table.
Pipeline Architecture (2)
- The Decision Before the Door Closes - hard - The window to stop it is smaller than you think.
- The What-If Machine - hard - A million slots. A thousand campaigns. Every combination matters.