Shadowing Practice: Interview with Big Data engineer in 2026. - Learn English Speaking with Video
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We built a real -time pipeline
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So leadership can ignore insights at millisecond speeds
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What was the question?
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Okay, sorry.
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I had quick
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Problem in database, but no worries all 200 tetabytes are recovered
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Big data most companies don't actually have big data
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They have medium data.
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Big data is anything that crushes Excel.
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We actually have two big data for fault tolerance.
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Two wrongs don't make a right, except in a distributed database.
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Big data is different math.
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1 plus 1, 1 .9.
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95 % confidence interval.
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Our 15 million raw data set has 800 columns.
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The rows aren't wide, they are panoramic.
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If the joint fits in memory, it belongs in Postgres.
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Our architecture preserves every invariant except the budget.
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Our cloud bill was $340 ,000.
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We don't know if the processing even ran.
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That was just observability.
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We support real -time processing, of course.
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Unless the event arrives early, late, duplicated, malformed, reordered, eventual consistency was too hard.
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So we went with immediately inaccurate.
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70 % of records are accurate.
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It's higher than the weather forecast.
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The numbers are not wrong.
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They are early.
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Wait, two, three, maybe four days, they will be late.
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It's almost interactive analytics.
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Final numbers mean numbers we have stopped refreshing.
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The slide says we handle billions of events.
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It does not say we handle them well.
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It is only truly idempotent if all availability zones go down equally during the outage.
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Management.
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Management asked us to build a data lake, but it wasn't scalable enough.
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So McKinsey asked us to build a data swamp.
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The project was declared successful before all the metrics arrived.
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We call that watermarking.
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Dashboard is green because the job that checks if the dashboard is wrong is red.
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Ah, what happened here?
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Let me quickly roll back 30 billion events.
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A production workaround becomes durable the moment the engineer who wrote it leaves.
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Yes.
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We removed an unused column and it broke Portugal.
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The bug has existed for eight years.
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At this point it's an interface.
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Quick Slack message.
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20 terabytes lost again.
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This is our architecture.
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Very simple.
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Kafka, Airflow, Databricks, Flink, Spark, SQL, Iceberg, S3, Presto, DBT.
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What does DBT stands for dialect behavioral therapy.
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We need that to avoid going crazy.
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We have the most modern stack in the industry.
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Only 10 % is COBOL.
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HDFS is not dead.
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It's waiting for someone with root access.
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We migrated from Kroon to Airflow for reliability.
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Then we wrote a Kroon job to check if Airflow silently died.
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We would switch from Databricks to Excel if it wasn't for date parsing.
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We are a data driven company of course.
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Every week somebody reads the invoices out of PDFs and types the data into Excel.
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Running on Kubernetes.
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We moved from Hive tables to Iceberg tables because we wanted the metadata to fail with better governance.
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Last week, we had some ransomware attack.
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We lost the backups, yes.
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Whenever we lose a backup, we reconstruct what the customer did from the logs.
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No, that's one of our industry's best practices.
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Our customers didn't even know.
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To be honest, most of our customers don't even use our product anyway.
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The board deck says petabyte scale, yeah.
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Scale is a direction, not a quantity.
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I checked with a legal.
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Management says one petabyte.
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I checked, yeah.
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We only process 18 terabytes, but we round up.
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Our P99 is four minutes.
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But the P50 is excellent.
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And most people are median.
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Streaming gets simple once you understand watermarks.
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Event time, processing time, state, back pressure.
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Batch and streaming produce different numbers.
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We average them.
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Our recommendation pipeline had three hours of Kafka lag.
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So technically it was a real time communication for your past self.
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Kafka rebalanced so often I started listing it under team building activities.
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We decoupled storage and compute.
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Now the storage team and the compute team have separate outages.
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Ah, again, we lost the logs from Tuesday.
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The data team, the data team has excellent isolation.
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We haven't spoken to product in seven months.
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All problems become your problems at one terabyte an hour.
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Exactly once processing is easy.
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You just need two topics, transactions, offsets, recovery state and a relaxed interpretation of easy.
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GDPR in a data warehouse.
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This is a funny joke.
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We anonymize the data by removing the column name.
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We persist it in places nobody knows how to query.
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The only thing in this company with strong durability is a bad architectural decision.
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Salary, job, security, holidays, pick two, a CIP compliant.
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Can we have this by Friday?
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In distributed systems, what does Friday mean?
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Before the meeting is only a partial order.
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The project isn't late.
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The clocks just disagree.
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It's a distributed organization.
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Every quarter we solve capacity problems by increasing input.
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We maintain system availability by shedding JIRA tickets.
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Last year, they fired 80 % of our team as part of our operational transformation.
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They should have used CRDTs instead.
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A backfill is when you fix one historical bug by introducing a brand new historical bug.
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The Snowflake warehouse runs a two -second query every minute.
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A very sophisticated way of never letting it turn off.
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Artificial intelligence?
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No. We still rely on humans, a single point of failure.
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Yes, David.
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The game.
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You pull something from the bottom, everything falls apart.
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It's educational game for industry.
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Back 2016, learning Hadoop in the simple 760 steps.
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That's right.
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Hadoop certified.
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Cloudera certified.
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Cloudera no longer offers this cert.
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We migrated to Abachi iceberg this year.
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Quick 43 months migration.
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We still use protobuf.
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Yes, we are still confused, but at least confused strongly type.
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Some say data is the new oil.
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We cannot stop producing it and we will pay to clean it up for years.
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From what I see, data is the new asbestos.
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The AI team spent four million and it called investment.
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I spent three hundred forty thousand.
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It is called a review.
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I'm in FinOps review every Thursday.
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The AI team has never ever been to FinOps.
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They have a different word for money.
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My cluster is a cost center.
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Their cluster is a strategy.
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Same rack in AWS where I make, there are my glasses.
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Duh!
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Ah, only disk usage 80%.
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This is sweet spot.
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A soft outage is when the checkpoint directory grows faster than S3 versioning can build.
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Back in the days, big data means you bring the intelligence to the data.
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That's why I go straight to big data center.
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We have two big data centers for fault tolerance.
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I wanted to become simple app developer.
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Take app, build it, host it on railway, no problems.
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No thinking required.
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I can go on holidays.
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But the team came with Airflow Graph.
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We use what?
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1, 2, 3, 4, 13, 14, 23, 60, 400 services just to clean the locks.
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Whole dashboard?
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You need whole company.
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I am on call today, yes.
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As you can see.
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Oh, I turn my phone off.
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If it burns, it burns.
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I don't have keys to service anyway.
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What am I gonna do?
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I'm not ignoring Slack.
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I'm just following our load shedding policy.
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Don't ship late and don't ship too early.
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Ship peacefully.
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Thank you, Railway, for sponsoring this video.
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Woordenschat en spreektips bij deze les
Deze spreekles is gebaseerd op de video “Interview with Big Data engineer in 2026”. Deze video bevat 168 zinnen en 1183 woorden om na te spreken. Het gesproken deel duurt 8:34. De spreker praat in een gelijkmatig tempo van ongeveer 138 woorden per minuut, prettig om te shadowen. Slechts 76% van de woorden hoort bij de 3.000 meest gebruikte Engelse woorden, dus de woordenschat is pittig.
Belangrijke woorden in deze video
15 woorden uit de video die het leren waard zijn, met uitspraak en betekenis:
| Woord | Uitspraak | Betekenis |
|---|---|---|
| distribute werkwoord | /dɪˈstɹɪbjuːt/ | verdelen |
| ignore werkwoord | /ɪɡˈnɔː/ | negeren |
| confused bijvoeglijk naamwoord | /kənˈfjuːzd/ | verward, in de war |
| railway zelfstandig naamwoord | /ˈɹeɪlˌweɪ/ | spoorwegen |
| architecture zelfstandig naamwoord | /ˈɑː.kɪˌtɛk.t͡ʃə/ | architectuur, bouwstijl |
| log zelfstandig naamwoord | /lɔɡ/ | boomstam, boomstronk |
| column zelfstandig naamwoord | /ˈkɒləm/ | zuil, kolom |
| database zelfstandig naamwoord | /ˈdeɪtəˌbeɪs/ | database, databank |
| backup zelfstandig naamwoord | /ˈbækˌʌp/ | reserve |
| availability zelfstandig naamwoord | /əˌveɪ.ləˈbɪl.ɪ.ti/ | beschikbaarheid, voorhanden zijn |
| warehouse zelfstandig naamwoord | /ˈwɛə(ɹ)haʊs/ | pakhuis, opslagplaats |
| tolerance zelfstandig naamwoord | /ˈtɑ.lə.ɹəns/ | verdraagzaamheid, tolerantie |
| pipeline zelfstandig naamwoord | /ˈpaɪpˌlaɪn/ | pijpleiding, pijplijn |
| cluster zelfstandig naamwoord | /ˈklʌstɚ/ | tros |
| query zelfstandig naamwoord | /ˈkwɪɹ.i/ | vraag, verzoek |
Phrasal verbs die je zult horen
| Woord | Betekenis |
|---|---|
| fall apart werkwoord | uiteenvallen, uit elkaar vallen |
| go down werkwoord | afdalen |
| turn off werkwoord | uitzetten, uitschakelen |
Zinnen om te herhalen
Korte, volledige zinnen uit de video die je in alledaagse gesprekken kunt gebruiken:
- We don't know if the processing even ran.
- No, that's one of our industry's best practices.
- Our customers didn't even know.
- We haven't spoken to product in seven months.
- What am I gonna do?
Grammatica in deze video
De structuren die de spreker het meest gebruikt, met de exacte woorden uit de video:
| Structuur | In de video |
|---|---|
| Present perfect have/has + voltooid deelwoord — iets uit het verleden dat nu nog telt | have stopped · has existed · haven't spoken |
| Lijdende vorm be + voltooid deelwoord — het gaat om wat er gebeurt, niet om wie het doet | are recovered · was declared · is called |
Uitspraak om op te letten
De spreker gebruikt 17 samentrekkingen en verkorte vormen, zoals don't, I'm, wasn't. Spreek ze kort uit, zoals je ze hoort.
- De klanken “sh” en “zh”: artificial /ˌɑː.tɪˈfɪʃ.əl/, interpretation /ɪnˌtɜːpɹəˈteɪʃən/, operational /ˌɑ.pəˈɹeɪ.ʃə.nəl/, transaction /tɹænˈzækʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/
- Lange woorden — let op de klemtoon: architecture /ˈɑː.kɪˌtɛk.t͡ʃə/, availability /əˌveɪ.ləˈbɪl.ɪ.ti/, artificial /ˌɑː.tɪˈfɪʃ.əl/, interpretation /ɪnˌtɜːpɹəˈteɪʃən/, operational /ˌɑ.pəˈɹeɪ.ʃə.nəl/
Klanken die Nederlandstaligen lastig vinden:
- Stemhebbende eindmedeklinker — /b/, /d/, /g/, /z/, /v/ niet verscherpen: confused /kənˈfjuːzd/, log /lɔɡ/, cloud /ˈklaʊ̯d/, solve /sɒlv/, arrive /əˈɹaɪv/
- /æ/ — opener dan de Nederlandse “e”: backup /ˈbækˌʌp/, salary /ˈsæləɹi/, relax /ɹɪˈlæks/, transaction /tɹænˈzækʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/
- /g/ — een harde plofklank, geen Nederlandse “g”: ignore /ɪɡˈnɔː/, log /lɔɡ/, migration /maɪˈɡɹeɪʃ(ə)n/, disagree /dɪsəˈɡɹi/, governance /ˈɡʌvəɹnəns/
Zo oefen je met deze video
- Luister de hele video één keer zonder te spreken en noteer de woorden die je niet kent.
- Spreek zin voor zin na op normale snelheid en herhaal elke zin tot je ritme gelijk is aan dat van de spreker.
- Neem jezelf op en vergelijk met het origineel; let daarbij op woorden als distribute, ignore, confused.
Wat is de Shadowing-techniek?
Shadowing is een wetenschappelijk onderbouwde taalleermethode die oorspronkelijk is ontwikkeld voor professionele tolkentraining en gepopulariseerd door polyglot Dr. Alexander Arguelles. De methode is eenvoudig maar krachtig: je luistert naar native Engelse audio en herhaalt het onmiddellijk hardop — als een schaduw die de spreker volgt met slechts 1–2 seconden vertraging. In tegenstelling tot passief luisteren of grammaticadrills, dwingt shadowing je hersenen en mondspieren om echte spraakpatronen tegelijkertijd te verwerken en te reproduceren. Onderzoek toont aan dat het de uitspraaknauwkeurigheid, intonatie, ritme, verbonden spraak, luisterbegrip en spreekvaardigheid aanzienlijk verbetert — waardoor het een van de meest effectieve methoden is voor IELTS Speaking-voorbereiding en echte Engelse communicatie.