Openingloading the content…

Loadingone moment…

Finance, Payments & Fintech

JP Morgan Chase

Banking / financial services · Data Engineering interview

Broad five-round loop: Java + big data, SQL/Python coding, PySpark, AWS/Terraform, and a VP + Executive Director finish.

Cloud / platform

AWS (+ Terraform); Spark, Java/Scala, internal platforms

Reported difficulty

Not reported

JavaSparkSQLPythonAWSTerraform

Hiring process

Screening

Java + big data (~1h45m)

Coding (SQL + Python)

VP techno-managerial

Executive Director

Offer

Round-by-round breakdown

Java / Big Data

Medium confidence

Core Java, Java concurrency, big-data concepts
Python: hash function, list comprehension, *args/**kwargs, OOP
Testing: unit/integration/regression, mock

SQL

High confidence

Recursion; window functions
RANK vs ROW_NUMBER; LEAD and LAG
Joins, UNION vs UNION ALL, stored procedures

PySpark

High confidence

Join two dataframes, filter country = Singapore, pivot, show the city with highest people count on top (window functions)
Architecture, dataframe, file formats

Cloud / AWS / Terraform

Medium confidence

Write Terraform to configure an EC2 machine
Explain the Terraform lifecycle for deploying a new cluster on AWS

System & pipeline design prompts

Banking data pipeline (Spark + AWS): correctness, lineage, governance

Prep — high priority

SQL (rank vs row_number, lead/lag, recursion, joins, union)
PySpark (join/filter/pivot/window, architecture, file formats)
Java core + concurrency

Prep — medium priority

AWS + Terraform (EC2, lifecycle)
Python fundamentals + testing types
Banking pipeline design

Rejection patterns

Weak Java/concurrency (when team is Java-based)
Shaky SQL window/rank-vs-row_number
No AWS/Terraform exposure
Many-round fatigue

Reported experiences

Data Engineer

ReportedFirst-hand

5 rounds: screening → Java + big data (~1h45m) → SQL+Python coding → VP techno-managerial → Executive Director. Real Qs: rank vs row_number, lead/lag, recursion; Java concurrency; Spark architecture/file formats; Terraform EC2 + lifecycle; PySpark join+filter(Singapore)+pivot+window.

Rehearse for JP Morgan Chase

Answered questions on what JP Morgan Chase actually asks — each with the short answer, the answer that gets you rejected, and the follow-up.

Then build one and have it reviewed: design a daily orders pipeline or model a marketplace. No account.

All interview experiences

Openingloading the content…

Finance, Payments & Fintech

JP Morgan Chase

Banking / financial services · Data Engineering interview

Broad five-round loop: Java + big data, SQL/Python coding, PySpark, AWS/Terraform, and a VP + Executive Director finish.

Cloud / platform

AWS (+ Terraform); Spark, Java/Scala, internal platforms

Reported difficulty

Not reported

JavaSparkSQLPythonAWSTerraform

Hiring process

Screening

Java + big data (~1h45m)

Coding (SQL + Python)

VP techno-managerial

Executive Director

Offer

Round-by-round breakdown

Java / Big Data

Medium confidence

Core Java, Java concurrency, big-data concepts
Python: hash function, list comprehension, *args/**kwargs, OOP
Testing: unit/integration/regression, mock

SQL

High confidence

Recursion; window functions
RANK vs ROW_NUMBER; LEAD and LAG
Joins, UNION vs UNION ALL, stored procedures

PySpark

High confidence

Join two dataframes, filter country = Singapore, pivot, show the city with highest people count on top (window functions)
Architecture, dataframe, file formats

Cloud / AWS / Terraform

Medium confidence

Write Terraform to configure an EC2 machine
Explain the Terraform lifecycle for deploying a new cluster on AWS

System & pipeline design prompts

Banking data pipeline (Spark + AWS): correctness, lineage, governance

Prep — high priority

SQL (rank vs row_number, lead/lag, recursion, joins, union)
PySpark (join/filter/pivot/window, architecture, file formats)
Java core + concurrency

Prep — medium priority

AWS + Terraform (EC2, lifecycle)
Python fundamentals + testing types
Banking pipeline design

Rejection patterns

Weak Java/concurrency (when team is Java-based)
Shaky SQL window/rank-vs-row_number
No AWS/Terraform exposure
Many-round fatigue

Reported experiences

Data Engineer

ReportedFirst-hand

Rehearse for JP Morgan Chase

Answered questions on what JP Morgan Chase actually asks — each with the short answer, the answer that gets you rejected, and the follow-up.

Then build one and have it reviewed: design a daily orders pipeline or model a marketplace. No account.

All interview experiences