Jpmorgan Interview Questions (9+ Questions)

Linux Log File Discovery Task: Use find and wc to recursively count all .log files under /var, including nested application log directories, and write only the total number of log files to /home/devops/log_count.txt. This hands-on Linux sysadmin and DevOps assessment evaluates your ability to work with real-world log management scenarios, mastering filesystem traversal, command-line automation, and audit-ready reporting for large-scale log retention and cleanup planning.

Reduce storage overhead and accelerate builds by aligning Dockerfiles to share common layers across application versions. Diagnose layer differences using docker history, understand how instruction order and base images affect layer reuse, eliminate metadata inconsistencies, and achieve sub-3-layer variance between versions. Essential for multi-version deployments, registry optimization, container versioning strategies, and efficient image storage in production environments.

def can_complete_circuit(gas: list[int], cost: list[int]) -> int:
if sum(gas) < sum(cost):
return -1

current_tank = 0
start_index = 0

for i in range(len(gas)):
    current_tank += gas[i] - cost[i]
    
    if current_tank < 0:
        start_index = i + 1
        current_tank = 0
        
return start_index

Practice a medium difficulty Snowflake SQL interview question tagged JPMorgan that tests deduplication, CTEs, and INNER JOIN. In a manufacturing scenario, you must remove duplicate rows from two tables using SELECT DISTINCT or ROW_NUMBER before joining them on a shared key. This question evaluates your ability to handle data quality issues before performing joins, a skill commonly tested in financial services and data engineering interviews.

Master data cleansing techniques in PySpark. Learn how to filter invalid primary keys, use regular expressions for date validation, and drop duplicate records before performing relational joins.

import heapq
from collections import defaultdict

class TopKFrequent:
def init(self, k):
self.k = k
self.freq = defaultdict(int)

def add(self, num):
    self.freq[num] += 1

def topK(self):
    items = [(-count, num) for num, count in self.freq.items()]
    top = heapq.nsmallest(self.k, items)
    return [num for _, num in top]

SELECT
card_name,
MAX(issued_amount) - MIN(issued_amount) AS issued_difference
FROM
card_issuance
GROUP BY
card_name
ORDER BY
issued_difference DESC;

WITH
ranked AS (
SELECT
card_name,
issued_amount,
ROW_NUMBER() OVER (
PARTITION BY
card_name
ORDER BY
issue_year,
issue_month
) AS rn
FROM
monthly_cards_issued
)
SELECT
card_name,
issued_amount
FROM
ranked
WHERE
rn = 1
ORDER BY
issued_amount DESC;

Fetch and parse HTML from a web page, extract all hyperlinks, filter external domains excluding the source domain, and save unique results to a text file using Python and BeautifulSoup.