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Data engineering interview · Media, Streaming & Telecom

Comcast

SQL (joins, SCD, window), Spark/Python/Scala, and a Hadoop→Spark batch+streaming migration design with sub-3-minute freshness.

Stages: 53 with reported questions
Difficulty: Not rated
Cloud: AWS (+ Azure/GCP)
Evidence: 1 of 2sources are first-hand

What Comcast does

And what its data engineers work with.

Business: Telecom / media / streaming
Platform: AWS (+ Azure/GCP); Presto, Hive, Spark
Stack named in its interviews: SQL
Spark
Python
Scala
AWS
Presto
Hive

The loop

Stages in the order candidates meet them.

01Recruiter
02Technical screen (1h)
03Second recruiter call
04Onsite loop
05Offer

5 stages. 3 rounds have reported questions, described below.

What each round expects

The topics it covers and the questions candidates reported.

ROUND 01
Technical screen
1 hour
Medium confidence
- SQL
1 reported question. See them below
ROUND 02
SQL
High confidence
- SQL
- Modeling
2 reported questions. See them below
ROUND 03
Spark / Python / Scala
Medium confidence
- SQL
- Spark
- Python
- Cloud and tools
2 reported questions. See them below

Reported interview questions

By round. Questions marked Expected are written from the company's standards.

Reported from accounts and guides, by round

Technical screenMedium confidence

Comcast data systems, ETL pipelines, SQLPractise SQL

SQLHigh confidence

Joins, SCD types, window functionsPractise SQL
Top-N per group, dedup, running totalsPractise SQL

Spark / Python / ScalaMedium confidence

Hands-on coding: SQL queries, ETL implementationPractise SQL
Tools: AWS, Presto, HivePractise Apache Spark

Expected written from Comcast's standards

Nobody reported these exact questions at Comcast. They are the questions a loop for each of its top topics is known to ask, so prepare for them as likely, not as confirmed.

Return the top 3 rows per group, and say what happens on ties.SQL
Find the latest row per key in a table that has duplicates.SQL
Design a star schema for orders, and state the grain first.Modeling
How do you keep history when a customer's address changes?Modeling
What is a shuffle, and how would you make a job shuffle less?Spark
One hot key makes a join slow. What do you do?Spark
When would you choose Airflow, and when would you not?Cloud and tools
How do you load files from object storage into a warehouse?Cloud and tools
Group events into sessions with a 30-minute gap.Python
Count by key in a file bigger than memory.Python

Must know

Ranked by how much of the evidence points at each topic.

SQLReported3 reported questions across 3 rounds
Data modelingReported1 reported question across 1 round
Spark and big dataIn the prioritiesNamed in the prep priorities
Cloud and toolsReported1 reported question across 1 round
Python and codingReported1 reported question across 1 round
Pipeline and system designIn the prioritiesNamed in the prep priorities

What matters most

Do the first group before the second.

SQL (joins, SCD types, window functions)
Do first (3)
Spark batch+streaming design (Hadoop migration, freshness SLA)
Data modeling (SCD, star/snowflake)
Python/Scala ETL; AWS/Presto/Hive
Then
Data quality stories

Rejection patterns

Why candidates were turned down, as reported.

Weak SCD/data-modeling
Modeling is named in 14 of 50 company accounts.
Cannot design batch+streaming migration
Design is named in 27 of 50 company accounts.
No data-quality/scalability reasoning
Design is named in 27 of 50 company accounts.

Reported experiences

4 reported, 1 composite. Each opens and closes. Composites are labelled.

5 accounts

Data Engineer (India)Date not statedNo offer (positive)Jointaro (2023)
Recruiter call, a technical screen and an onsite loop.
What to take from it The loop is a standard three-stage shape.
Data EngineerChennai, IndiaGlassdoor
In Chennai: two technical rounds and a manager round. The first was about solving problems and designing a pipeline. The second covered past experience and how you make decisions.
What to take from it Be ready to explain how you decide between options.
Data EngineerDate not statedGlassdoor
Questions reported: an SQL scenario and a Python question, joins, types of slowly changing dimensions, window functions, and tuning an ETL pipeline, including the challenges and how you got past them.
What to take from it Prepare one ETL tuning story with the challenges.
Questions named
- Joins and window functions
- SCD types
- Optimise an ETL pipeline: challenges and how you overcame them
Data EngineerDate not statedGlassdoor
Earlier interviews focused on past projects, so be ready to walk through your own work. One reviewer reported a very rude hiring manager.
What to take from it Be able to explain your own projects clearly.
Composite walkthroughs. Built from the company's documented loop, not from one person's account.
The Technical screen roundDate not statedComposite
This is a composite, not one person's account. It is built from the loop we have on record for Comcast. 1 hour. Questions reported for this round: Comcast data systems, ETL pipelines, SQL.
What to take from it Practise these questions before you reach this round.
Questions named
- Comcast data systems, ETL pipelines, SQL

Sources and how sure we are

The Hadoop→Spark batch+streaming migration (sub-3-minute freshness) is the signature design prompt.

JoinTaro — Comcast Data Engineer, India (Jun 2023)
InterviewQuery — Comcast Data Engineer guide (guide, not a first-hand account)

Rehearse the Comcast loop

Their reported questions, one at a time, against a stopwatch.

Technical screen · 1 of 5

Comcast data systems, ETL pipelines, SQL

Out loud, in order: clarify, build it, check it, explain it.

Practise SQL

00:00

Your preparation plan

Pick your level and the weeks you have.

Built from what Comcast asks, strongest first. For the wider basics at your level, follow the Mid level plan alongside it.

Week 1
SQL
Read: SQL chapters Drill: SQL practice Say it aloud: SQL questions Full plan: Ace the SQL round
Data modeling
Read: Data modeling chapters Drill: Modeling practice Say it aloud: Data modeling questions Full plan: Ace the modeling round
Spark and big data
Read: Spark chapters Drill: Spark playground Say it aloud: Spark questions Full plan: Ace the Spark round
Cloud and tools
Read: Data pipeline chapters Say it aloud: AWS questions
Python and coding
Read: Python chapters Drill: Python practice Say it aloud: Python questions Full plan: Ace the Python round
Pipeline and system design
Read: Data pipeline chapters Drill: Pipeline practice Say it aloud: Data pipeline questions Full plan: Ace the pipeline round
Week 2
Rehearse the Comcast loop
Run the question deckThen repeat your weakest topic once more.

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All interview experiences

Data engineering interview · Media, Streaming & Telecom

Comcast

SQL (joins, SCD, window), Spark/Python/Scala, and a Hadoop→Spark batch+streaming migration design with sub-3-minute freshness.

Stages: 53 with reported questions
Difficulty: Not rated
Cloud: AWS (+ Azure/GCP)
Evidence: 1 of 2sources are first-hand

What Comcast does

And what its data engineers work with.

Business: Telecom / media / streaming
Platform: AWS (+ Azure/GCP); Presto, Hive, Spark
Stack named in its interviews: SQL
Spark
Python
Scala
AWS
Presto
Hive

The loop

Stages in the order candidates meet them.

01Recruiter
02Technical screen (1h)
03Second recruiter call
04Onsite loop
05Offer

5 stages. 3 rounds have reported questions, described below.

What each round expects

The topics it covers and the questions candidates reported.

ROUND 01
Technical screen
1 hour
Medium confidence
- SQL
1 reported question. See them below
ROUND 02
SQL
High confidence
- SQL
- Modeling
2 reported questions. See them below
ROUND 03
Spark / Python / Scala
Medium confidence
- SQL
- Spark
- Python
- Cloud and tools
2 reported questions. See them below

Reported interview questions

By round. Questions marked Expected are written from the company's standards.

Reported from accounts and guides, by round

Technical screenMedium confidence

Comcast data systems, ETL pipelines, SQLPractise SQL

SQLHigh confidence

Joins, SCD types, window functionsPractise SQL
Top-N per group, dedup, running totalsPractise SQL

Spark / Python / ScalaMedium confidence

Hands-on coding: SQL queries, ETL implementationPractise SQL
Tools: AWS, Presto, HivePractise Apache Spark

Expected written from Comcast's standards

Nobody reported these exact questions at Comcast. They are the questions a loop for each of its top topics is known to ask, so prepare for them as likely, not as confirmed.

Return the top 3 rows per group, and say what happens on ties.SQL
Find the latest row per key in a table that has duplicates.SQL
Design a star schema for orders, and state the grain first.Modeling
How do you keep history when a customer's address changes?Modeling
What is a shuffle, and how would you make a job shuffle less?Spark
One hot key makes a join slow. What do you do?Spark
When would you choose Airflow, and when would you not?Cloud and tools
How do you load files from object storage into a warehouse?Cloud and tools
Group events into sessions with a 30-minute gap.Python
Count by key in a file bigger than memory.Python

Must know

Ranked by how much of the evidence points at each topic.

SQLReported3 reported questions across 3 rounds
Data modelingReported1 reported question across 1 round
Spark and big dataIn the prioritiesNamed in the prep priorities
Cloud and toolsReported1 reported question across 1 round
Python and codingReported1 reported question across 1 round
Pipeline and system designIn the prioritiesNamed in the prep priorities

What matters most

Do the first group before the second.

SQL (joins, SCD types, window functions)
Do first (3)
Spark batch+streaming design (Hadoop migration, freshness SLA)
Data modeling (SCD, star/snowflake)
Python/Scala ETL; AWS/Presto/Hive
Then
Data quality stories

Rejection patterns

Why candidates were turned down, as reported.

Weak SCD/data-modeling
Modeling is named in 14 of 50 company accounts.
Cannot design batch+streaming migration
Design is named in 27 of 50 company accounts.
No data-quality/scalability reasoning
Design is named in 27 of 50 company accounts.

Reported experiences

4 reported, 1 composite. Each opens and closes. Composites are labelled.

5 accounts

Data Engineer (India)Date not statedNo offer (positive)Jointaro (2023)
Recruiter call, a technical screen and an onsite loop.
What to take from it The loop is a standard three-stage shape.
Data EngineerChennai, IndiaGlassdoor
In Chennai: two technical rounds and a manager round. The first was about solving problems and designing a pipeline. The second covered past experience and how you make decisions.
What to take from it Be ready to explain how you decide between options.
Data EngineerDate not statedGlassdoor
Questions reported: an SQL scenario and a Python question, joins, types of slowly changing dimensions, window functions, and tuning an ETL pipeline, including the challenges and how you got past them.
What to take from it Prepare one ETL tuning story with the challenges.
Questions named
- Joins and window functions
- SCD types
- Optimise an ETL pipeline: challenges and how you overcame them
Data EngineerDate not statedGlassdoor
Earlier interviews focused on past projects, so be ready to walk through your own work. One reviewer reported a very rude hiring manager.
What to take from it Be able to explain your own projects clearly.
Composite walkthroughs. Built from the company's documented loop, not from one person's account.
The Technical screen roundDate not statedComposite
This is a composite, not one person's account. It is built from the loop we have on record for Comcast. 1 hour. Questions reported for this round: Comcast data systems, ETL pipelines, SQL.
What to take from it Practise these questions before you reach this round.
Questions named
- Comcast data systems, ETL pipelines, SQL

Sources and how sure we are

The Hadoop→Spark batch+streaming migration (sub-3-minute freshness) is the signature design prompt.

JoinTaro — Comcast Data Engineer, India (Jun 2023)
InterviewQuery — Comcast Data Engineer guide (guide, not a first-hand account)

Rehearse the Comcast loop

Their reported questions, one at a time, against a stopwatch.

Technical screen · 1 of 5

Comcast data systems, ETL pipelines, SQL

Out loud, in order: clarify, build it, check it, explain it.

Practise SQL

00:00

Your preparation plan

Pick your level and the weeks you have.

Built from what Comcast asks, strongest first. For the wider basics at your level, follow the Mid level plan alongside it.

Week 1
SQL
Read: SQL chapters Drill: SQL practice Say it aloud: SQL questions Full plan: Ace the SQL round
Data modeling
Read: Data modeling chapters Drill: Modeling practice Say it aloud: Data modeling questions Full plan: Ace the modeling round
Spark and big data
Read: Spark chapters Drill: Spark playground Say it aloud: Spark questions Full plan: Ace the Spark round
Cloud and tools
Read: Data pipeline chapters Say it aloud: AWS questions
Python and coding
Read: Python chapters Drill: Python practice Say it aloud: Python questions Full plan: Ace the Python round
Pipeline and system design
Read: Data pipeline chapters Drill: Pipeline practice Say it aloud: Data pipeline questions Full plan: Ace the pipeline round
Week 2
Rehearse the Comcast loop
Run the question deckThen repeat your weakest topic once more.

What Comcast does

The loop

What each round expects

Technical screen

SQL

Spark / Python / Scala

Reported interview questions

Reported from accounts and guides, by round

Expected written from Comcast's standards

Must know

What matters most

Rejection patterns

Reported experiences

Questions named

Questions named

Rehearse the Comcast loop

Your preparation plan

Week 1

Week 2

What Comcast does

The loop

What each round expects

Technical screen

SQL

Spark / Python / Scala

Reported interview questions

Reported from accounts and guides, by round

Expected written from Comcast's standards

Must know

What matters most

Rejection patterns

Reported experiences

Questions named

Questions named

Rehearse the Comcast loop

Your preparation plan

Week 1

Week 2