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Databricks·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Databricks SWE interview with a networking/systems problem that had more layers to it than I expected. The core question was manageable but the follow-ups kept coming and I felt like I was scrambling by the end.

Questions Asked (4)

Q1

You're given an ordered list of firewall rules in CIDR notation, each marked allow or deny. Given an IP address as input, determine whether it's allowed or blocked. First matching rule wins.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

The base case wasn't bad.

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AI HintsAI Generated

Suggested Approach

Clarify the input format and constraints, then propose an efficient algorithm that converts IP addresses to integers and uses binary search or a trie for fast lookups. Discuss trade-offs between preprocessing time, memory usage, and query speed, and consider edge cases like overlapping rules and IPv6.

Pro tip: Mention that in production systems like Databricks, firewall rules are often stored in a trie or interval tree to handle millions of rules with low latency, and that you'd consider caching frequent lookups.

1. Clarify requirements and constraints

Ask about the number of rules, expected query frequency, IP version (IPv4/IPv6), and whether rules can be updated dynamically. This determines the optimal data structure and algorithm.

2. Choose data representation

Convert CIDR blocks and IP addresses to integer ranges for IPv4 (or 128-bit integers for IPv6) to simplify comparisons. Represent each rule as a start and end integer with an allow/deny action.

3. Design efficient lookup

For static rules, sort rules by start address and use binary search to find the first rule whose range contains the IP. Alternatively, build a trie or interval tree for O(log n) or O(1) lookups.

4. Handle first-match semantics

Ensure the lookup returns the first matching rule in the original order. If using sorting, store the original index and compare indices when multiple rules match.

5. Discuss trade-offs and edge cases

Compare preprocessing time vs. query time, memory usage, and support for dynamic updates. Address edge cases like no matching rule (default deny/allow), overlapping rules, and IPv6.

Key Points to Mention

  • Converting IP addresses and CIDR blocks to integers for efficient range comparisons
  • Using binary search on sorted rules or a trie for O(log n) or O(1) lookup
  • Handling first-match semantics by preserving original rule order
  • Trade-offs between preprocessing (sorting/trie construction) and query performance
  • Edge cases: no matching rule, overlapping rules, IPv4 vs IPv6, and dynamic rule updates
  • Scalability considerations for millions of rules and high query throughput

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

What test cases would you write for this firewall rule lookup?

Algorithms & Data Structures
Author's notes

Blanked for a second then just started listing edge cases out loud.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the firewall rule lookup problem: inputs (IP, port, protocol, etc.), outputs (allow/deny), and rule representation (CIDR ranges, priorities). Then systematically cover functional, boundary, and performance test cases, including overlapping rules and edge cases like empty rules or invalid inputs.

Pro tip: Mention that test cases should also cover rule precedence and conflict resolution, as real firewalls often have overlapping rules where order matters. Also, consider scalability: test with large rule sets to ensure the lookup remains efficient.

1. Clarify requirements and assumptions

Ask about the input format (e.g., IP address, port, protocol), rule structure (CIDR, port ranges, actions), and expected output (allow/deny). Confirm if rules have priorities or if order matters.

2. Identify functional test cases

Cover basic allow/deny scenarios: exact match, no match, match with wildcards, and multiple rules. Include cases where the packet matches multiple rules to test precedence.

3. Cover boundary and edge cases

Test IP boundaries (e.g., first/last IP in a CIDR block), port boundaries (0, 65535), empty rule set, invalid inputs (malformed IP, negative port), and IPv4 vs IPv6.

4. Include performance and scalability tests

Test with a large number of rules (e.g., 10k+) to ensure lookup time is acceptable. Consider worst-case scenarios like many overlapping rules or no match requiring full scan.

5. Consider integration and security aspects

Test how the lookup integrates with other components (e.g., rule updates, caching). Also, think about security: ensure default deny, no unintended allows, and resistance to injection attacks.

Key Points to Mention

  • Rule precedence and conflict resolution (e.g., first match vs. most specific match)
  • Boundary conditions for IP addresses and ports (e.g., /32, /0, port 0, 65535)
  • Handling of invalid or malformed inputs (e.g., non-numeric port, invalid CIDR)
  • Performance with large rule sets and worst-case lookup scenarios
  • IPv4 vs IPv6 and mixed environments
  • Default behavior when no rule matches (e.g., default deny)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q3

How would you extend the solution to accept a CIDR block as input instead of a single IP address?

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

This one actually interested me.

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AI HintsAI Generated

Suggested Approach

First, clarify the current solution's interface and assumptions, then propose generalizing it to accept a CIDR block by parsing the prefix length and iterating over the address range. Discuss trade-offs between enumerating all IPs versus using range-based operations, and consider edge cases like IPv4 vs IPv6 and large blocks.

Pro tip: Mention that for large CIDR blocks (e.g., /8), enumerating all IPs is infeasible, so you'd need to adapt the algorithm to work with ranges or use a trie/interval tree. This shows awareness of scalability and real-world constraints.

1. Clarify the current solution

Ask or state what the existing solution does with a single IP address, including its input/output and any assumptions (e.g., IPv4 only, data structures used).

2. Parse and validate CIDR input

Explain how to parse a CIDR block (e.g., '192.168.1.0/24') into a network address and prefix length, and validate it (e.g., using a library or manual bit manipulation).

3. Adapt the algorithm for ranges

Describe how to extend the logic to handle a range of IPs, either by iterating over all addresses (if small) or by modifying the algorithm to process the range as a whole (e.g., using interval arithmetic or a trie).

4. Address scalability and trade-offs

Discuss performance implications: for large CIDR blocks, enumeration is impractical, so consider alternative approaches like lazy evaluation, streaming, or range-based queries. Mention time/space complexity.

5. Handle edge cases and extensions

Cover edge cases such as /0, /32, IPv6, overlapping blocks, and how the solution would integrate with existing code. Optionally, mention testing strategies.

Key Points to Mention

  • CIDR notation and prefix length (e.g., /24 means 256 addresses)
  • IP address as a 32-bit integer (or 128-bit for IPv6) for range calculations
  • Trade-off between enumerating all IPs vs. processing the range as a single entity
  • Scalability concerns for large blocks (e.g., /8 has 16M addresses)
  • Use of data structures like tries, interval trees, or sorted arrays for efficient range queries
  • Edge cases: /0, /32, IPv6, non-network-aligned addresses, and input validation

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q4

Write pseudocode for the IP lookup against the firewall rule list.

Algorithms & Data StructuresSystem Design
Author's notes

Pretty straightforward once the logic was clear.

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AI HintsAI Generated

Suggested Approach

First, clarify the firewall rule semantics (e.g., first-match vs. best-match, CIDR ranges, ports, protocols) and the expected input/output. Then, outline a pseudocode solution that iterates through rules in priority order, checking if the packet's IP (and possibly port/protocol) matches each rule, and returns the action of the first matching rule or a default action.

Pro tip: Mention that in production systems, rules are often stored in a trie or interval tree for O(log n) lookup, but for pseudocode, a linear scan is acceptable if you note the trade-off and potential optimizations.

1. Clarify requirements

Ask about rule format (e.g., CIDR, wildcards), matching criteria (source/destination IP, port, protocol), and action (allow/deny). Confirm if first-match or best-match semantics apply.

2. Define data structures

Represent each rule as a struct with fields like ip_range, port_range, protocol, and action. Store rules in an ordered list (priority order) or a more efficient structure like a trie.

3. Design matching logic

For a given packet, iterate through rules in order. For each rule, check if the packet's IP falls within the rule's IP range (using CIDR matching) and if other criteria (port, protocol) match.

4. Return action

If a rule matches, return its action (e.g., ALLOW or DENY). If no rule matches, return the default action (usually DENY).

5. Write pseudocode

Express the algorithm in clear pseudocode, using functions like ipInRange(ip, cidr) and considering edge cases (e.g., empty rule list, invalid IP).

Key Points to Mention

  • CIDR notation and how to check if an IP is in a subnet (e.g., bitwise AND with subnet mask).
  • Rule ordering and first-match semantics (common in firewalls like iptables).
  • Handling of default policy when no rules match.
  • Potential optimizations: using a trie, interval tree, or caching for faster lookups.
  • Edge cases: invalid IP, overlapping rules, rule with wildcard (0.0.0.0/0).
  • Time complexity: O(n) for linear scan, O(log n) for optimized structures.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.