Prática de Shadowing: Interview with Big Data engineer in 2026. - Aprenda a falar inglês com vídeo
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168 frases
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1
We built a real -time pipeline
2
So leadership can ignore insights at millisecond speeds
3
What was the question?
4
Okay, sorry.
5
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.
32
The slide says we handle billions of events.
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It does not say we handle them well.
34
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.
41
Ah, what happened here?
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Let me quickly roll back 30 billion events.
43
A production workaround becomes durable the moment the engineer who wrote it leaves.
44
Yes.
45
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.
49
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.
96
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.
101
Salary, job, security, holidays, pick two, a CIP compliant.
102
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.
108
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.
111
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.
113
The Snowflake warehouse runs a two -second query every minute.
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A very sophisticated way of never letting it turn off.
115
Artificial intelligence?
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No. We still rely on humans, a single point of failure.
117
Yes, David.
118
The game.
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You pull something from the bottom, everything falls apart.
120
It's educational game for industry.
121
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.
126
We migrated to Abachi iceberg this year.
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Quick 43 months migration.
128
We still use protobuf.
129
Yes, we are still confused, but at least confused strongly type.
130
Some say data is the new oil.
131
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.
133
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.
138
They have a different word for money.
139
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.
142
Duh!
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Ah, only disk usage 80%.
144
This is sweet spot.
145
A soft outage is when the checkpoint directory grows faster than S3 versioning can build.
146
Back in the days, big data means you bring the intelligence to the data.
147
That's why I go straight to big data center.
148
We have two big data centers for fault tolerance.
149
I wanted to become simple app developer.
150
Take app, build it, host it on railway, no problems.
151
No thinking required.
152
I can go on holidays.
153
But the team came with Airflow Graph.
154
We use what?
155
1, 2, 3, 4, 13, 14, 23, 60, 400 services just to clean the locks.
156
Whole dashboard?
157
You need whole company.
158
I am on call today, yes.
159
As you can see.
160
Oh, I turn my phone off.
161
If it burns, it burns.
162
I don't have keys to service anyway.
163
What am I gonna do?
164
I'm not ignoring Slack.
165
I'm just following our load shedding policy.
166
Don't ship late and don't ship too early.
167
Ship peacefully.
168
Thank you, Railway, for sponsoring this video.
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Vocabulário e dicas de fala para esta lição
Esta aula de conversação usa o vídeo “Interview with Big Data engineer in 2026”. Este vídeo tem 168 frases e 1183 palavras para praticar shadowing. A fala dura 8:34. O falante mantém um ritmo estável de cerca de 138 palavras por minuto, confortável para o shadowing. Apenas 76% das palavras estão entre as 3.000 mais comuns do inglês, por isso o vocabulário é exigente.
Vocabulário principal deste vídeo
15 palavras do vídeo que vale a pena aprender, com pronúncia e significado:
| Palavra | Pronúncia | Significado |
|---|---|---|
| distribute verbo | /dɪˈstɹɪbjuːt/ | distribuir, parcelar |
| ignore verbo | /ɪɡˈnɔː/ | ignorar |
| confused adjetivo | /kənˈfjuːzd/ | confuso |
| railway substantivo | /ˈɹeɪlˌweɪ/ | ferrovia |
| architecture substantivo | /ˈɑː.kɪˌtɛk.t͡ʃə/ | arquitetura |
| log substantivo | /lɔɡ/ | tora |
| column substantivo | /ˈkɒləm/ | coluna |
| database substantivo | /ˈdeɪtəˌbeɪs/ | banco de dados, base de dados |
| backup substantivo | /ˈbækˌʌp/ | backup, becape |
| availability substantivo | /əˌveɪ.ləˈbɪl.ɪ.ti/ | disponibilidade |
| warehouse substantivo | /ˈwɛə(ɹ)haʊs/ | armazém |
| tolerance substantivo | /ˈtɑ.lə.ɹəns/ | tolerância |
| pipeline substantivo | /ˈpaɪpˌlaɪn/ | ducto, duto |
| cluster substantivo | /ˈklʌstɚ/ | aglomeração, aglomerado |
| query substantivo | /ˈkwɪɹ.i/ | pergunta |
Phrasal verbs que você vai ouvir
| Palavra | Significado |
|---|---|
| fall apart verbo | cair aos pedaços |
| go down verbo | descer |
| turn off verbo | desligar, apagar |
Frases que vale a pena repetir
Frases curtas e completas do vídeo que você pode usar na conversa do dia a dia:
- 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?
Gramática neste vídeo
As estruturas que o falante mais usa, com as palavras exatas do vídeo:
| Estrutura | No vídeo |
|---|---|
| Present perfect have/has + particípio passado — uma ação passada que ainda importa agora | have stopped · has existed · haven't spoken |
| Voz passiva be + particípio passado — o foco está no que acontece, não em quem faz | are recovered · was declared · is called |
Pronúncia para ficar de olho
O falante usa 17 contrações e formas reduzidas, como don't, I'm, wasn't. Diga-as na forma curta, do jeito que você ouve.
- Os sons de “sh” e “zh”: artificial /ˌɑː.tɪˈfɪʃ.əl/, interpretation /ɪnˌtɜːpɹəˈteɪʃən/, operational /ˌɑ.pəˈɹeɪ.ʃə.nəl/, transaction /tɹænˈzækʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/
- Palavras longas — acerte a sílaba tônica: architecture /ˈɑː.kɪˌtɛk.t͡ʃə/, availability /əˌveɪ.ləˈbɪl.ɪ.ti/, artificial /ˌɑː.tɪˈfɪʃ.əl/, interpretation /ɪnˌtɜːpɹəˈteɪʃən/, operational /ˌɑ.pəˈɹeɪ.ʃə.nəl/
Sons difíceis para falantes de português:
- Consoante final — sem acrescentar um “i” depois: distribute /dɪˈstɹɪbjuːt/, confused /kənˈfjuːzd/, log /lɔɡ/, backup /ˈbækˌʌp/, topic /ˈtɑpɪk/
- /l/ final — a língua toca o céu da boca, não vira “u”: artificial /ˌɑː.tɪˈfɪʃ.əl/, operational /ˌɑ.pəˈɹeɪ.ʃə.nəl/, partial /ˈpɑɹʃəl/, architectural /ˌɑɹkɪˈtɛkt͡ʃəɹəl/, behavioral /bɪˈheɪvjəɹəl/
- /h/ — um sopro suave, diferente do “r”: warehouse /ˈwɛə(ɹ)haʊs/, behavioral /bɪˈheɪvjəɹəl/
Como praticar com este vídeo
- Ouça o vídeo inteiro uma vez sem falar e anote as palavras que você não conhece.
- Faça shadowing frase por frase na velocidade normal, repetindo cada uma até o seu ritmo ficar igual ao do falante.
- Grave a sua voz e compare com o original, prestando atenção a palavras como distribute, ignore, confused.
O que é a Técnica de Shadowing?
Shadowing é uma técnica de aprendizado de idiomas com base científica, originalmente desenvolvida para o treinamento de intérpretes profissionais. O método é simples, mas poderoso: você ouve áudio em inglês nativo e repete imediatamente em voz alta — como uma sombra seguindo o falante com 1-2 segundos de atraso. Pesquisas mostram melhora significativa na precisão da pronúncia, entonação, ritmo, sons conectados, compreensão auditiva e fluência na fala.