Oracle Coding Interview Questions: DS&A, Java & SQL

Oracle hires engineers at scale, especially new grads and for Oracle Cloud Infrastructure (OCI), and its coding interview reflects that: medium-difficulty data-structures-and-algorithms, often in Java, with occasional SQL and lower-level questions. It's more approachable than the FAANG bar, but consistency and fundamentals are tested thoroughly.

Here's the full loop with four worked problems and what Oracle's interviewers look for.

The full interview process

Stage	Format	Notes
Recruiter / OA	Screen + sometimes an online test	DS&A, occasionally SQL
Technical phone screen	45 min	1-2 medium problems, often in Java
Onsite coding (2-3)	45-60 min each	DS&A, trees, some SQL/design
System design (mid/senior)	45 min	Scalable service for OCI-style roles
Behavioral / hiring manager	30-45 min	Team fit, fundamentals depth

Move Zeroes (two pointers)

Question: Move all zeros to the end while keeping the order of non-zero elements, in place.

A write pointer; swap each non-zero element into the write position and advance it.

def moveZeroes(nums):
    write = 0
    for read in range(len(nums)):
        if nums[read] != 0:
            nums[write], nums[read] = nums[read], nums[write]
            write += 1

O(n) time, O(1) space, single pass. The two-scan (count then fill) version also works but the one-pass swap is what's expected.

Valid Parentheses (stack)

Question: Given a string of brackets, determine if they are validly matched and nested.

Push opening brackets; on a closing bracket, verify it matches the top of the stack. An empty stack at the end means valid.

def isValid(s):
    pairs = {')': '(', ']': '[', '}': '{'}
    stack = []
    for ch in s:
        if ch in pairs:
            if not stack or stack.pop() != pairs[ch]:
                return False
        else:
            stack.append(ch)
    return not stack

O(n) time, O(n) space. Edge cases graded: a closing bracket with an empty stack, and a non-empty stack at the end.

Merge Two Sorted Lists

Question: Merge two sorted linked lists into one sorted list.

A dummy head and a tail pointer; repeatedly attach the smaller of the two front nodes.

def mergeTwoLists(l1, l2):
    dummy = tail = ListNode(0)
    while l1 and l2:
        if l1.val <= l2.val:
            tail.next, l1 = l1, l1.next
        else:
            tail.next, l2 = l2, l2.next
        tail = tail.next
    tail.next = l1 or l2
    return dummy.next

O(m+n) time, O(1) extra. The dummy head avoids special-casing the first node.

Kth Largest Element (heap)

Question: Find the kth largest element in an unsorted array.

A min-heap of size k; the root is the kth largest after processing all elements.

import heapq
def findKthLargest(nums, k):
    heap = nums[:k]
    heapq.heapify(heap)
    for n in nums[k:]:
        if n > heap[0]:
            heapq.heapreplace(heap, n)
    return heap[0]

O(n log k) time, O(k) space — better than sorting when k is small. Quickselect gives O(n) average if asked.

Patterns Oracle asks most

Pattern	Frequency	Note
Arrays & strings	~30% of loops	Approachable mediums
Linked lists	~15%	Reverse, merge, cycle
Trees / BFS-DFS	~20%	Traversals, BST
Heap / sorting	~15%	Kth largest, top-k
SQL	~10%	Joins, aggregation for data roles
Dynamic programming	~10%	Basic sequence DP

Common pitfalls specific to Oracle

• Rusty Java fundamentals. Many Oracle rounds are in Java — brush up on collections, generics, and equals/hashCode.
• Ignoring SQL. For data-leaning roles, a SQL round (joins, group-by) is common; don't skip it.
• Inconsistent edge cases. Oracle's bar is reliability across mediums, not one hard solve.
• Underprepping system design for OCI/cloud roles, which lean on it more than typical product teams.

A 4-week prep plan for an Oracle loop

1. Week 1: Arrays, strings, and linked lists — the approachable core, in your strongest language.
2. Week 2: Trees, heaps, and (for data roles) SQL joins and aggregation.
3. Week 3: Mixed mediums for consistency plus light system design for OCI roles.
4. Week 4: Behavioral prep and a solo mock.

FAQ

What is the Oracle coding interview like?

Approachable medium data-structures-and-algorithms, frequently in Java, with occasional SQL and lower-level questions. Oracle hires at scale (especially new grads and for Oracle Cloud Infrastructure), so the bar emphasizes reliable fundamentals over exotic hard problems.

Does Oracle ask SQL in coding interviews?

For data-leaning and database-adjacent roles, yes - expect a SQL round covering joins, aggregation, and grouping. Pure software roles focus more on DS&A, but brushing up on SQL basics is worthwhile given Oracle's database heritage.

Is Oracle easier than FAANG to interview at?

The individual coding problems generally skew easier than the FAANG bar, but Oracle still tests fundamentals thoroughly and values consistency across multiple rounds. For new grads it's one of the higher-volume, more approachable big-tech pipelines.

What language should I use for Oracle interviews?

Java is common given Oracle's stack, and many rounds are conducted in it, but you can usually use your strongest language. If you choose Java, be solid on collections, generics, and the equals/hashCode contract.

Can CoPilot Interview help me prepare for Oracle?

Yes. It returns optimal solutions with Big-O in your chosen language - including idiomatic Java - so you can drill Oracle's medium bank until it's automatic. Follow Oracle's interview rules during the live round.