DSA Interview Roadmap
Data Engineer
A Data Engineer interview leans on 196 of the 370 curated problems. The other 174 are lower frequency for this role, still here, just not first.
Heavy on arrays, sorting, and math for ETL-style problems; graphs and DP show up far less than in general SDE loops.
- Focus on
- 196
- Core topics
- 7
- Deprioritise
- 174
- Full catalogue
- 370
Track your progress on this roadmap: the map fills itself as you solve.
Start freeWhat this interview looks like
Pipeline interviews revolve around processing partitioned file sets, orchestrating stages, and synchronizing distributed transforms. You will be asked to partition large record batches, resolve timestamp collisions, and join out-of-order streams. The bar is guaranteeing idempotent batch operations, understanding skew, and writing dependable sorting logic across heterogeneous schema records.
What it leans away from
Pointer-heavy linked structures and recursive backtracking search get de-emphasized, since analytical engines operate on columnar chunks rather than individual heap nodes. Infrastructure teams maintaining orchestration schedulers or lineage metadata graphs sometimes still require acyclic dependency traversal.
Beyond the coding round
This roadmap only orders the DSA problems a Data Engineer interview draws on. The role itself also expects:
The whole path
- Phase 1 - DSA Foundation
- Phase 2 - Role Skill Gaps
- Phase 3 - Projects and Interview Proof
Phase 1 - DSA Foundation
The curation places 7 core topics first for this role, leading with practice problems.
- 6 problemsVisualize
Phase 2 - Role Skill Gaps
The curation balances theory and practice equally across these role-specific topics to complete the 196 focus problems.
Phase 3 - Projects and Interview Proof
The curation pushes 174 problems down for this role, so understanding the theory is the goal here.
How the Data Engineer path differs from other roles
DSA interviews are mapped per role rather than shared. Here is how the topic priorities on the Data Engineer path compare with other career paths:
Distinctive core topics
Core in this path, but core in fewer than half of all roles.
Lower priority here than usual
Core in more than half of all roles, but lower priority for this path.
No widely shared core topics are deprioritised for this role.
Closest roles
Roles with the highest overlap in core topics.
Ready to actually walk this path?
Every topic above links to real problems, step-by-step pattern visualizers, and an in-browser compiler. Your progress tracks automatically as you solve.
Data Engineer DSA questions, answered
How many DSA problems does a Data Engineer need to solve?
About 196 of the 370 curated problems. Those sit in the 7 topics a Data Engineer interview leans on; the remaining 174 are lower frequency for this role and are worth doing later rather than first.
Which DSA topics matter most for a Data Engineer?
Arrays, Sorting, Math, Matrix, Intervals, Two Pointers and others: the core tier for this role. Topic priority is mapped per role rather than shared, so a Data Engineer path deliberately differs from a generic sheet order.
Can a Data Engineer skip some DSA topics?
Deprioritise rather than skip. 174 of the 370 problems are lower frequency for a Data Engineer, so they belong after the core tier: not never, but not first. Interviews do occasionally reach outside the common ground.
Is this Data Engineer roadmap free?
Yes. The roadmap, the problem list, the pattern walkthroughs and progress tracking are all free with no signup required to read. Only AI-generated insights are metered.
Other role roadmaps
Problem set and role mapping as of .