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Datavant Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Datavant, you play a foundational role in building the technology that connects health data securely across the healthcare ecosystem. Your daily work directly impacts products designed to protect patient privacy while enabling critical health data interoperability, bridging fragmented systems, and accelerating medical research. By developing robust pipelines, cloud infrastructure, and scalable APIs, you help solve some of the most complex data liquidity challenges in healthcare. The work at Datavant combines high technical scale with strict regulatory and security demands. You will contribute to core products dealing with real-world health data ingestion, transformation, and matching, requiring you to write clean, resilient code that performs reliably under tight constraints.

This guide is scoped to a Software Engineer candidate at Datavant.

Focus areas

  • Debugging
  • CSV Data Processing
  • System Design

The Datavant interview process

Datavant candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screening

Initial screening to assess candidate's background and fit for the role.

What to demonstrate

  • Initial screening to assess candidate's background and fit for the role
  • Depth in Debugging

How to prepare

  • Be able to walk your CV end to end in two minutes, and say why this company specifically.
  • Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.

Technical Assessments

Candidates complete coding challenges and system design tasks to evaluate technical skills.

What to demonstrate

  • Candidates complete coding challenges and system design tasks to evaluate technical skills
  • Depth in Debugging

How to prepare

  • Answer aloud and timed: Review a CSV processing script with multiple nested classes to identify why data is read into dictionary structures rather than flat row lists.
  • Answer aloud and timed: Fix issues in a data-loading module where incorrect handling of file separators causes runtime exceptions.

Behavioral Interviews

Interviews focused on past experiences and cultural alignment with the team.

What to demonstrate

  • Interviews focused on past experiences and cultural alignment with the team
  • Depth in Debugging

How to prepare

  • Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
  • Re-read the description of the behavioral interviews above and write down what you would ask to confirm before it.

Where candidates lose points

Embrace Collaborative Debugging

Treat debugging rounds as a pair-programming exercise where you talk through your hypotheses, test assumptions, and welcome feedback from the interviewer.

Ask Proactive Questions in System Design

Because initial system design prompts are intentionally minimal, take the lead in asking about scale, data formats, and consumers before diving into your architecture.

Master the Basics Over Complex Tricks

Focus your coding practice on writing clean, working solutions to standard string and list problems rather than memorizing obscure algorithmic edge cases.

Prepare Concrete Examples for Behavioral Rounds

Have 3 to 4 detailed stories ready from your past experience highlighting project ownership, technical trade-offs, and cross-functional collaboration.

Demonstrate Domain Awareness

Familiarize yourself with the unique challenges of health data interoperability, privacy, and secure data sharing to show genuine interest in the company's mission.

Questions & practice

Fix issues in a data-loading module where incorrect handling of file separators causes runtime exceptions.

Medium · Technical Debugging and Refactoring

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

1–2 sentences introducing the category and what it tests. These questions test your command of data structures

Medium · Algorithmic and Coding Exercises

1–2 sentences introducing the category and what it tests. These questions test your command of data structures, string manipulation, and your ability to write working code iteratively.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Solve a string rotation problem (e.g., verifying if one string is a rotation of another) and discuss alternati

Medium · Algorithmic and Coding Exercises

Solve a string rotation problem (e.g., verifying if one string is a rotation of another) and discuss alternative comparison approaches.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Given a list, move an item from position x to position y in-place without altering the overall size of the lis

Medium · Algorithmic and Coding Exercises

Given a list, move an item from position x to position y in-place without altering the overall size of the list during traversal.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Implement custom equality methods or data structures using test-driven development (TDD) approaches.

Medium · Algorithmic and Coding Exercises

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Implement a custom Set data structure with a focus on edge cases like item removal operations.

Medium · Algorithmic and Coding Exercises

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Work through a series of LeetCode-style questions that incrementally build on previous solutions during the vi

Medium · Algorithmic and Coding Exercises

Work through a series of LeetCode-style questions that incrementally build on previous solutions during the virtual onsite.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Hold a per-tenant active cap against concurrent creates

Hard · write skew · isolation levels · constraints

A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.

Approach

  1. Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
  2. Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
  3. Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
  4. State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.

Follow-up

  • A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
  • The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?

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

  1. 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.
  2. 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.
  3. 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.
  4. 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?

1–2 sentences introducing the category and what it tests. This section assesses your capacity to design scalab

Medium · System Design and Architecture

1–2 sentences introducing the category and what it tests. This section assesses your capacity to design scalable, domain-specific systems using collaborative text-based documentation or structured assumptions.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Design a system in the healthcare domain to calculate specific public health metrics (e.g., vaccination percen

Medium · System Design and Architecture

Design a system in the healthcare domain to calculate specific public health metrics (e.g., vaccination percentages across COVID-19 populations).

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Propose an architecture for ingesting and processing disparate health data feeds while ensuring data integrity

Medium · System Design and Architecture

Propose an architecture for ingesting and processing disparate health data feeds while ensuring data integrity and security.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Outline a scalable API design for clients querying distributed patient record tokens without violating privacy

Medium · System Design and Architecture

Outline a scalable API design for clients querying distributed patient record tokens without violating privacy protocols.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Define data schemas and storage strategies for handling large-scale medical coding edits and denials data.

Medium · System Design and Architecture

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Structure a cloud infrastructure setup supporting secure virtual desktop environments for remote engineering t

Medium · System Design and Architecture

Structure a cloud infrastructure setup supporting secure virtual desktop environments for remote engineering teams.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Discuss how you handle ambiguity when given minimal product requirements or open-ended system design prompts.

Medium · Behavioral and Cultural Alignment

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

1–2 sentences introducing the category and what it tests. This category evaluates your ability to read pre-wri

Medium · Technical Debugging and Refactoring

1–2 sentences introducing the category and what it tests. This category evaluates your ability to read pre-written codebases, diagnose logic errors, and write clean fixes under time pressure.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Debug a 300-line class that loads and modifies CSV data, finding the root cause of failing test cases and pars

Medium · Technical Debugging and Refactoring

Debug a 300-line class that loads and modifies CSV data, finding the root cause of failing test cases and parsing issues.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Review a CSV processing script with multiple nested classes to identify why data is read into dictionary struc

Medium · Technical Debugging and Refactoring

Review a CSV processing script with multiple nested classes to identify why data is read into dictionary structures rather than flat row lists.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Refactor a legacy data ingestion pipeline to improve readability and maintainability without altering existing

Medium · Technical Debugging and Refactoring

Refactor a legacy data ingestion pipeline to improve readability and maintainability without altering existing functionality.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Trace through an unfamiliar codebase during a live screen to isolate and patch edge-case failures.

Medium · Technical Debugging and Refactoring

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Suggested practice checklist

Built from the rounds and topics Datavant candidates report.

Day 1 — Map the Datavant loop

  • Write out the reported sequence: Recruiter Screening, Technical Assessments, Behavioral Interviews.
  • 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 3 reported rounds, with the weakest marked.

Day 2 — Work Debugging

  • Spend the session on Debugging, which Datavant candidates report being tested on.
  • Write one worked example in Debugging and time yourself on it.

Deliverable: One timed worked example in Debugging.

Day 3 — Work CSV Data Processing

  • Spend the session on CSV Data Processing, which Datavant candidates report being tested on.
  • Write one worked example in CSV Data Processing and time yourself on it.

Deliverable: One timed worked example in CSV Data Processing.

Day 4 — Work System Design

  • Spend the session on System Design, which Datavant candidates report being tested on.
  • Write one worked example in System Design and time yourself on it.

Deliverable: One timed worked example in System Design.

Day 5 — Answer out loud: Technical Debugging and Refactoring

  • Answer aloud, timed: 1–2 sentences introducing the category and what it tests. This category evaluates your ability to read pre-written codebases, diagnose logic errors, and write clean fixes under time pressure.
  • Answer aloud, timed: Debug a 300-line class that loads and modifies CSV data, finding the root cause of failing test cases and parsing issues.

Deliverable: Spoken answers to 2 reported Technical Debugging and Refactoring question(s), under time.

Day 6 — Answer out loud: Algorithmic and Coding Exercises

  • Answer aloud, timed: 1–2 sentences introducing the category and what it tests. These questions test your command of data structures, string manipulation, and your ability to write working code iteratively.
  • Answer aloud, timed: Solve a string rotation problem (e.g., verifying if one string is a rotation of another) and discuss alternative comparison approaches.

Deliverable: Spoken answers to 2 reported Algorithmic and Coding Exercises question(s), under time.

Day 7 — Answer out loud: System Design and Architecture

  • Answer aloud, timed: 1–2 sentences introducing the category and what it tests. This section assesses your capacity to design scalable, domain-specific systems using collaborative text-based documentation or structured assumptions.
  • Answer aloud, timed: Design a system in the healthcare domain to calculate specific public health metrics (e.g., vaccination percentages across COVID-19 populations).

Deliverable: Spoken answers to 2 reported System Design and Architecture question(s), under time.

Behavioural preparation

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

1–2 sentences introducing the category and what it tests. These conversations gauge your career history, colla

Medium · Behavioral and Cultural Alignment

1–2 sentences introducing the category and what it tests. These conversations gauge your career history, collaboration style, and alignment with the company's operating principles.

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?

Walk through a challenging engineering project you owned from conception to deployment.

Medium · Behavioral and Cultural Alignment

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 you had to make technical trade-offs under tight deadlines and how you communicated those risk

Medium · Behavioral and Cultural Alignment

Describe a time you had to make technical trade-offs under tight deadlines and how you communicated those risks.

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?

Explain why you want to work specifically at Datavant and how your background aligns with health data connecti

Medium · Behavioral and Cultural Alignment

Explain why you want to work specifically at Datavant and how your background aligns with health data connectivity.

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?

Share an experience where you collaborated across cross-functional teams to resolve a production bottleneck.

Medium · Behavioral and Cultural Alignment

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?