Shadowing Practice: Interview with Big Data engineer in 2026. - Learn English Speaking with Video
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168 sentences
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1
We built a real -time pipeline
2
So leadership can ignore insights at millisecond speeds
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What was the question?
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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.
20
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.
26
It's higher than the weather forecast.
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The numbers are not wrong.
28
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.
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.
37
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.
49
20 terabytes lost again.
50
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.
61
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.
67
We lost the backups, yes.
68
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.
70
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.
94
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.
98
We anonymize the data by removing the column name.
99
We persist it in places nobody knows how to query.
100
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?
104
Before the meeting is only a partial order.
105
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.
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.
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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.
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.
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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.
133
The AI team spent four million and it called investment.
134
I spent three hundred forty thousand.
135
It is called a review.
136
I'm in FinOps review every Thursday.
137
The AI team has never ever been to FinOps.
138
They have a different word for money.
139
My cluster is a cost center.
140
Their cluster is a strategy.
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Same rack in AWS where I make, there are my glasses.
142
Duh!
143
Ah, only disk usage 80%.
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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.
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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?
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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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Vocabulary and speaking notes for this lesson
This speaking lesson is built on the video “Interview with Big Data engineer in 2026”. This video has 168 sentences and 1183 words to shadow. The speech runs for 8:34. The speaker talks at a steady 138 words per minute, a comfortable pace for shadowing. Only 76% of the words are among the 3,000 most common in English, so the vocabulary is demanding.
Key vocabulary in this video
15 words from the video worth learning, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| distribute verb | /dɪˈstɹɪbjuːt/ | To divide into portions and dispense. |
| ignore verb | /ɪɡˈnɔː/ | To deliberately not listen or pay attention to. |
| confused adjective | /kənˈfjuːzd/ | unable to think clearly or understand |
| railway noun | /ˈɹeɪlˌweɪ/ | A transport system using rails used to move passengers or goods. |
| architecture noun | /ˈɑː.kɪˌtɛk.t͡ʃə/ | The art and science of designing and managing the construction of buildings and other structures, particularly if they are well proportioned and decorated. |
| log noun | /lɔɡ/ | The trunk of a dead tree, cleared of branches. |
| column noun | /ˈkɒləm/ | A solid upright structure designed usually to support a larger structure above it, such as a roof or horizontal beam, but sometimes for decoration. |
| database noun | /ˈdeɪtəˌbeɪs/ | A collection of (usually) organized information in a regular structure, usually but not necessarily in a machine-readable format accessible by a computer. |
| backup noun | /ˈbækˌʌp/ | A reserve or substitute. |
| availability noun | /əˌveɪ.ləˈbɪl.ɪ.ti/ | The quality of being available. |
| warehouse noun | /ˈwɛə(ɹ)haʊs/ | A facility for storing large amounts of merchandise or products. |
| tolerance noun | /ˈtɑ.lə.ɹəns/ | The ability or practice of tolerating; an acceptance of or patience with the beliefs, opinions or practices of others; a lack of bigotry. |
| pipeline noun | /ˈpaɪpˌlaɪn/ | A conduit made of pipes used to convey water, gas or petroleum, etc. |
| cluster noun | /ˈklʌstɚ/ | A bunch or group of several discrete items that are close to each other. |
| query noun | /ˈkwɪɹ.i/ | A question, an inquiry (US), an enquiry (UK). |
Phrasal verbs you will hear
| Word | Meaning |
|---|---|
| fall apart verb | To disintegrate, to break into pieces. |
| go down verb | To descend; to move from a higher place to a lower one. |
| roll back verb | To return to a prior state. |
| turn off verb | To power down, to switch off, to put out of operation, to deactivate (an appliance, light, mechanism, functionality etc.). |
Sentences worth repeating
Short, complete lines from the video that you can reuse in everyday conversation:
- 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?
Grammar in this video
The structures the speaker uses most, with the exact words from the video:
| Structure | In the video |
|---|---|
| Present perfect have/has + past participle — a past action that still matters now | have stopped · has existed · haven't spoken |
| Passive voice be + past participle — the focus is on what happens, not who does it | are recovered · was declared · is called |
Pronunciation to watch
The speaker uses 17 contractions and reduced forms, such as don't, I'm, wasn't. Say them the short way, as you hear them.
- The “sh” and “zh” sounds: artificial /ˌɑː.tɪˈfɪʃ.əl/, interpretation /ɪnˌtɜːpɹəˈteɪʃən/, operational /ˌɑ.pəˈɹeɪ.ʃə.nəl/, transaction /tɹænˈzækʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/
- Long words — get the stress right: architecture /ˈɑː.kɪˌtɛk.t͡ʃə/, availability /əˌveɪ.ləˈbɪl.ɪ.ti/, artificial /ˌɑː.tɪˈfɪʃ.əl/, interpretation /ɪnˌtɜːpɹəˈteɪʃən/, operational /ˌɑ.pəˈɹeɪ.ʃə.nəl/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Shadow it sentence by sentence at normal speed, repeating each one until your rhythm matches the speaker.
- Record yourself and compare with the original, paying attention to words like distribute, ignore, confused.
What is the Shadowing Technique?
Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.