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Synovus Financial Software Engineer Interview Guide

Synovus Financial Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

At Synovus Financial, a Software Engineer plays a critical role in bridging the gap between traditional banking reliability and modern digital innovation. As a leading financial services company, Synovus Financial relies heavily on its engineering team to build, maintain, and secure the digital infrastructure that services millions of retail and commercial customers. This role is not just about writing code; it is about building trust, ensuring transactional integrity, and creating seamless financial experiences. The engineering team at Synovus Financial works on a wide array of products, from customer-facing mobile and web banking applications to complex back-end payment processing systems, data pipelines, and internal cloud infrastructure.

This guide is scoped to a Software Engineer candidate at Synovus Financial.

Focus areas

Software Engineering (General)
Behavioral/Team Interaction Fit
Technical Interviewing Skills

The Synovus Financial interview process

Synovus Financial candidates report 2 rounds over 2-4 weeks. The stages below are what candidates describe, not a published process.

Telephonic Screening

Initial call focusing on your background, high-level technical experience, and career aspirations.

What to demonstrate

Initial call focusing on your background, high-level technical experience, and career aspirations
Depth in Software Engineering (General)

How to prepare

Answer aloud and timed: Explain the difference between an abstract class and an interface, and when you would use each.
Answer aloud and timed: How do you ensure data integrity and security when developing APIs that handle sensitive financial information?

Comprehensive Interview

In-depth interview conducted either face-to-face or via video panel, covering technical concepts, business analysis scenarios, and behavioral questions.

What to demonstrate

In-depth interview conducted either face-to-face or via video panel
Covering technical concepts, business analysis scenarios, and behavioral questions

How to prepare

Answer aloud and timed: Describe your experience with relational databases. How do you optimize a slow-running SQL query?
Answer aloud and timed: What is your approach to writing unit tests, and how do you ensure adequate code coverage before deployment?

Where candidates lose points

Emphasize your collaboration skills

Since many interviewers focus heavily on how you get along with the team, highlight your experiences working closely with others, resolving conflicts constructively, and contributing to a positive team culture.

Be ready for business-focused questions

Do not just focus on the technical details. Be prepared to discuss how your technical decisions impact business outcomes and how you collaborate with business analysts.

Showcase your adaptability

Synovus Financial is actively evolving its technology and plans. Demonstrating that you are flexible, open to change, and comfortable navigating evolving technical roadmaps will make you a highly attractive candidate.

Questions & practice

How do you explain complex technical concepts to non-technical stakeholders, such as business analysts or prod

Medium · Business Analysis & Problem Solving

How do you explain complex technical concepts to non-technical stakeholders, such as business analysts or product owners?

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
State the target complexity and say which constraint rules the naive version out.

Follow-up

How does this change if the input no longer fits in memory?
What is the worst case, and how likely is it on real data?

Canonicalise a request body into a stable idempotency fingerprint

Medium · parsing · canonicalisation · hashing

idempotency_key.request_fingerprint is a SHA-256 over the method, path and canonicalised body, and a retry whose fingerprint differs must be rejected with 422 rather than served the stored response. Write the canonicaliser. Bodies are JSON up to 256 KB nested at most 32 levels; clients vary key order, whitespace and unicode escaping, and some send 64-bit ids as JSON numbers. Produce a deterministic byte string such that semantically identical bodies match and any semantic difference does not. State your complexity and name two normalisations you refuse to perform.

Approach

Parse once into a tree, then re-serialise under fixed rules: object keys sorted, array order preserved, one escaping convention, no insignificant whitespace. Parsing is O(n) and sorting keys is O(k log k) per object, so O(n log n) overall with O(depth) stack, and the 32-level cap is enforced during parsing because hostile nesting is how a canonicaliser becomes a stack overflow.
Sort keys by their UTF-8 bytes and say why the obvious implementation is wrong in some runtimes: a default string comparison that orders by UTF-16 code units places surrogate pairs, meaning code points from U+10000 up, below U+E000 to U+FFFF, which is not UTF-8 byte order, so two services written in different languages disagree on the same document.
Do not re-encode numbers through a double. IEEE-754 binary64 represents integers exactly only up to 2^53, so normalising a 19-digit id through a float changes it, and 1 against 1.0 cannot be reconciled without deciding whether they are the same value. Preserve the literal token, and require ids as strings at the API boundary if you want them comparable.
Reject duplicate keys rather than picking one. JSON permits them and parsers disagree, most keeping the last, so any choice you make ties the fingerprint to a parser detail that the code handling the request does not necessarily share.

Follow-up

A client sends the same logical request with an extra field your API ignores. Same key, different fingerprint, so you return 422. Is that the right answer?
Where does the fingerprint get computed relative to request decompression and the body-size limit?

Collapse a redelivered event batch into per-aggregate high-water marks

Easy · hashing · at-least-once · aggregation

You drain a batch of up to 5,000,000 events, each (aggregate_id BIGINT, aggregate_version INT, event_type, payload). The log guarantees order within one aggregate only; the batch merges 64 partitions, and a relay failover has redelivered a range, so an older version for an aggregate can appear after a newer one. Given a map of last_applied_version per aggregate, produce the events worth applying, at most one per (aggregate_id, version), plus the count discarded. Target O(n) time. State the memory for 2,000,000 distinct aggregates and what you do when it does not fit.

Approach

One pass, one hash map from aggregate_id to the highest version kept, and a discard counter. An event whose version is at or below last_applied_version for its aggregate is dropped without further work, which is the whole reason the event carries its version rather than a delta. O(n) expected time, O(d) space in distinct aggregates.
Keep the maximum, never the last occurrence. The redelivered range means the final appearance of an aggregate in the batch can be an older version than one seen earlier in the same batch, so last-wins applies stale state over newer state and the projection regresses with no error anywhere.
Cost the memory instead of calling it large: an 8-byte key plus a 4-byte version is 12 bytes of payload, and an open-addressed table held at a 0.7 load factor costs roughly 17 bytes per entry before per-slot metadata, so 2,000,000 aggregates is tens of megabytes in a native layout and several times that in a runtime that boxes both key and value.
If the distinct set exceeds memory, partition on hash(aggregate_id) mod P and reduce each partition independently. Every event for one aggregate hashes to the same partition, so the per-partition result is exact and the merge is concatenation rather than a second reduction.

Follow-up

The payload is a patch rather than a snapshot, so applying only the highest version loses the intermediate changes. What changes in your reduction?
How do you detect that version 7 arrived while version 6 was never delivered, and what should the consumer do about the gap?

Describe your experience with relational databases. How do you optimize a slow-running SQL query?

Medium · Technical & Core Engineering

Approach

Name the grain you start from and join outward from it.
Check whether any join is one-to-many before aggregating, or the sums inflate.
Say which index the query would use, and what makes it unusable.
Handle the rows that do not match: that is usually the actual question.

Follow-up

How does the query change if that join becomes one-to-many?
What happens to this when the table is ten times larger?

Find version gaps and relay lag with window functions

Medium · window functions · event tables · frame semantics

outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.

Approach

Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.

Follow-up

Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?

Explain the difference between an abstract class and an interface, and when you would use each.

Medium · Technical & Core Engineering

Approach

Clarify what is being asked and what a complete answer contains.
State your assumptions explicitly before working the problem.
Say what you would check first and why it is the highest-information step.
Work from the requirement backwards to the design.

Follow-up

What assumption would you test first?
How would you know your answer was wrong?

How do you ensure data integrity and security when developing APIs that handle sensitive financial information

Medium · Technical & Core Engineering

How do you ensure data integrity and security when developing APIs that handle sensitive financial information?

Approach

Clarify what is being asked and what a complete answer contains.
State your assumptions explicitly before working the problem.
Say what you would check first and why it is the highest-information step.
Work from the requirement backwards to the design.

Follow-up

What assumption would you test first?
How would you know your answer was wrong?

What is your approach to writing unit tests, and how do you ensure adequate code coverage before deployment?

Medium · Technical & Core Engineering

Approach

Clarify what is being asked and what a complete answer contains.
State your assumptions explicitly before working the problem.
Say what you would check first and why it is the highest-information step.
Work from the requirement backwards to the design.

Follow-up

What assumption would you test first?
How would you know your answer was wrong?

p99 jumped on one listing filter while p50 stayed flat

Medium · query planning · composite index · percentiles

After a release that added an owner_user_id filter to the resource listing, p99 rose from 90 ms to 1.9 s while p50 stayed at 40 ms. Traffic and row counts are unchanged. resource carries the index (tenant_id, status, updated_at DESC, resource_id DESC). The new query filters tenant_id and owner_user_id, orders by updated_at DESC, resource_id DESC, and takes 20 rows. On PostgreSQL, explain the shape of the regression, prove it from a query plan, and give the index you would add.

Approach

Start from the shape. A flat p50 with a moved p99 means a subset of requests changed cost, not all of them, so the first job is naming the subset. Bucket the endpoint's latency by the tenant's row count; the natural hypothesis is that large tenants are a small share of requests and all of the tail.
Get the plan for the new query on a large tenant with EXPLAIN (ANALYZE, BUFFERS). Expect an index scan over the tenant's range, a filter discarding most of it, then a Sort feeding the Limit, possibly reporting Sort Method: external merge Disk. Read actual rows on the scan node, not estimated.
Explain why the existing index cannot serve it. A composite B-tree is seekable only as a left prefix, and with no equality predicate on status the scan cannot treat updated_at as an ordering, because rows in the tenant's range are ordered by status first. Everything matching must be read and sorted before LIMIT 20 can apply, so a tenant with 400,000 rows pays 400,000 rows to return 20.
Add (tenant_id, owner_user_id, updated_at DESC, resource_id DESC). Equality on the first two columns leaves the index ordered by updated_at within that pair, so the plan becomes an index scan that stops after 20 rows with no Sort node. PostgreSQL can scan a B-tree backwards, so the DESC markers matter only if the two sort columns ever disagree in direction; keeping them explicit documents the order the keyset cursor depends on.

Follow-up

The endpoint paginates with OFFSET. What does page 500 cost with your index, and what does the keyset version cost?
How would you have caught this before release, given that a 10,000-row seed database produces the same plan shape at an unnoticeable cost?

Suggested practice checklist

Built from the rounds and topics Synovus Financial candidates report.

Day 1 — Map the Synovus Financial loop

Write out the reported sequence: Telephonic Screening, Comprehensive Interview.
For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 2 reported rounds, with the weakest marked.

Day 2 — Work Software Engineering (General)

Spend the session on Software Engineering (General), which Synovus Financial candidates report being tested on.
Write one worked example in Software Engineering (General) and time yourself on it.

Deliverable: One timed worked example in Software Engineering (General).

Day 3 — Work Behavioral/Team Interaction Fit

Spend the session on Behavioral/Team Interaction Fit, which Synovus Financial candidates report being tested on.
Write one worked example in Behavioral/Team Interaction Fit and time yourself on it.

Deliverable: One timed worked example in Behavioral/Team Interaction Fit.

Day 4 — Work Technical Interviewing Skills

Spend the session on Technical Interviewing Skills, which Synovus Financial candidates report being tested on.
Write one worked example in Technical Interviewing Skills and time yourself on it.

Deliverable: One timed worked example in Technical Interviewing Skills.

Day 5 — Answer out loud: Technical & Core Engineering

Answer aloud, timed: Explain the difference between an abstract class and an interface, and when you would use each.
Answer aloud, timed: How do you ensure data integrity and security when developing APIs that handle sensitive financial information?

Deliverable: Spoken answers to 2 reported Technical & Core Engineering question(s), under time.

Day 6 — Answer out loud: Business Analysis & Problem Solving

Answer aloud, timed: How do you handle a situation where the business requirements provided for a feature are ambiguous or incomplete?
Answer aloud, timed: Describe a time when you had to balance technical debt with the urgent business need to deliver a feature quickly.

Deliverable: Spoken answers to 2 reported Business Analysis & Problem Solving question(s), under time.

Day 7 — Answer out loud: Behavioral & Team Collaboration

Answer aloud, timed: Tell me about a time you had a disagreement with a team member on a technical approach. How did you resolve it?
Answer aloud, timed: Describe your typical work style. Do you prefer working independently, or do you thrive in highly collaborative team environments?

Deliverable: Spoken answers to 2 reported Behavioral & Team Collaboration question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

How do you handle a situation where the business requirements provided for a feature are ambiguous or incomple

Medium · Business Analysis & Problem Solving

How do you handle a situation where the business requirements provided for a feature are ambiguous or incomplete?

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

Describe a time when you had to balance technical debt with the urgent business need to deliver a feature quic

Medium · Business Analysis & Problem Solving

Describe a time when you had to balance technical debt with the urgent business need to deliver a feature quickly.

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

Tell me about a time you had a disagreement with a team member on a technical approach. How did you resolve it

Medium · Behavioral & Team Collaboration

Tell me about a time you had a disagreement with a team member on a technical approach. How did you resolve it?

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

Describe your typical work style. Do you prefer working independently, or do you thrive in highly collaborativ

Medium · Behavioral & Team Collaboration

Describe your typical work style. Do you prefer working independently, or do you thrive in highly collaborative team environments?

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

Tell me about your background and work experience. What motivated you to apply to Synovus Financial?

Medium · Behavioral & Team Collaboration

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

How do you handle constructive feedback on your code during peer reviews?

Medium · Behavioral & Team Collaboration

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?