Question 1

Describe how you deploy code to a production environment using Jenkins

Accepted Answer

Situation: We shipped data pipelines weekly; manual deploys caused errors and rollbacks. Task: Automate build, test, deploy with safety gates. Action: Jenkins pipeline: checkout → build → test → deploy staging → smoke tests → manual approval for prod → deploy prod (rolling/blue-green). Declarative pipeline with stages; credentials in Jenkins, not code. Immutable tags; containers for consistency. Result: Zero manual deploy errors; rollback via prior tag....

Question 2

Explain the Terraform lifecycle for deploying a new cluster on AWS

Accepted Answer

Lifecycle: init (providers, backend) → plan (diff) → apply (create/update) → destroy (optional). For EMR: Define aws_emr_cluster, instance groups, security groups, IAM. Variables for sizing. Why: Reproducible; versioned....

Question 3

Write Terraform configurations for configuring an EC2 machine

Accepted Answer

**Example**: resource "aws_instance" "app" { ami = var.ami_id; instance_type = var.instance_type; subnet_id = aws_subnet.main.id; vpc_security_group_ids = [aws_security_group.app.id]; key_name = aws_key_pair.app.key_name; user_data = file("bootstrap.sh"); root_block_device { volume_size = 50 }; tags = { Name = "app-server" } }. **AMI**: data "aws_ami" "ubuntu" { most_recent = true; owners = ["099720109477"]; filter { name = "name"; values = ["ubuntu-jammy-*"] } }....

Question 4

Difference between stubs and skeletons in RMI (Remote Method Invocation)

Accepted Answer

**Why RMI Needs Proxies**: Clients invoke remote objects as if local; stubs/skeletons provide location transparency and serialization.

**Stub (Client-side)**: Proxy for remote object; marshals arguments, sends over network, unmarshals return. Acts as local representative.

**Skeleton (Server-side)**: Receives calls, unmarshals args, invokes real object, marshals result....

Question 5

Convert a Binary Search Tree (BST) into a skewed tree in either increasing or decreasing order

Accepted Answer

**Logic:** Inorder = sorted. Increasing: left→visit→right. Decreasing: reverse. **In-place:** Right=prev, left=None; update prev. O(n) time, O(h) stack. **Why:** BST degradation to list. **Production:** Rare; understand pointer manipulation.

Question 6

Explain the internal working of a HashMap

Accepted Answer

**Structure:** Array of buckets. Hash→index. **Collision:** Chaining (list) or open addressing. **Load factor:** Triggers resize. **Java:** hashCode(), equals(). **Complexity:** O(1) avg get/put; resize O(n). **Why:** Constant-time lookup....

Question 7

Finding Complete String Pairs - identify pairs of strings that when concatenated contain all 26 English alphabets

Accepted Answer

**Logic:** set(a)|set(b)==26 letters. **Brute:** O(n²). **Optimized:** 2^26 masks; group by mask; find complementary. O(n+2^26). **Why:** Bitmask for set. **Production:** Handle empty strings.

Question 8

Read data from three files into a Pandas DataFrame, perform transformations, remove columns, filter rows, search for strings

Accepted Answer

**Why This Pattern:** Multi-file concat + transform + filter is the core ETL pattern. At JP Morgan, regulatory data often comes as daily files—concat, validate, filter, load.

**Scalability:** pd.concat([df1,df2,df3]) loads all into memory. For 3 large files: read each with chunksize, concat chunks, process incrementally. Or use Dask for out-of-core....

JP Morgan Data Engineer Interview Questions

Reading isn't practice. Get AI feedback on your answers.

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JP Morgan Data Engineer Interview Questions

Reading isn't practice. Get AI feedback on your answers.

Other Companies