As a Software Engineer at Data Society, you play a pivotal role in developing innovative solutions that leverage data science and technology to solve complex problems. Your contributions will directly influence the design and functionality of products that empower users to harness data effectively. This role is not only about coding; it encompasses a deep understanding of user needs, scalability, and the strategic alignment of technology with business objectives. The impact of your work will be felt across various products and teams within Data Society, where you will collaborate closely with data scientists, product managers, and other engineers. You will tackle challenges that require creative problem-solving and a solid grasp of both software engineering principles and data-driven insights. Expect to work on projects that involve large datasets, real-time processing, and algorithm optimization, making your role both critical and intellectually stimulating.
Initial Screening
reportedAn initial review of the candidate's application and qualifications.
What to demonstrate
- An initial review of the candidate's application and qualifications
- Depth in BI Reporting (Business Intelligence)
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 Assessment
reportedA structured evaluation of the candidate's technical skills and problem-solving abilities.
What to demonstrate
- A structured evaluation of the candidate's technical skills and problem-solving abilities
- Depth in BI Reporting (Business Intelligence)
How to prepare
- Answer aloud and timed: How do you ensure the security of your applications?
- Answer aloud and timed: Explain the concept of RESTful APIs and their advantages.
Behavioral Interview
reportedAssessment of interpersonal skills and cultural fit within Data Society.
What to demonstrate
- Assessment of interpersonal skills and cultural fit within Data Society
- Depth in BI Reporting (Business Intelligence)
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 interview above and write down what you would ask to confirm before it.
Final Evaluation
reportedA comprehensive review of the candidate's performance across all interview stages.
What to demonstrate
- A comprehensive review of the candidate's performance across all interview stages
- Depth in BI Reporting (Business Intelligence)
How to prepare
- Answer aloud and timed: Write a function to reverse a linked list.
- Answer aloud and timed: How would you merge two sorted arrays?
Offer Discussion
reportedDiscussion regarding the job offer, including compensation and role expectations.
What to demonstrate
- Discussion regarding the job offer
- Including compensation and role expectations
How to prepare
- Answer aloud and timed: Describe a time you optimized a piece of code. What were the results?
- Answer aloud and timed: Solve a given problem using dynamic programming.
PracHub editorial advice for the preparation topics above.
Practice Coding Regularly
Regular coding practice is essential. Use platforms like LeetCode or HackerRank to sharpen your skills.
Understand the Company Values
Familiarize yourself with Data Society's mission and values, as aligning your answers to these will demonstrate your fit.
Prepare Examples
Have concrete examples ready that highlight your problem-solving skills and teamwork.
Ask Questions
Prepare thoughtful questions for your interviewers to demonstrate your genuine interest in the company and role.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Implement a function to find the longest substring without repeating characters.
Implement a function to find the longest substring without repeating characters.
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?
Write a function to reverse a linked list.
Write a function to reverse a linked list.
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?
How would you merge two sorted arrays?
How would you merge two sorted arrays?
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?
Solve a given problem using dynamic programming.
Solve a given problem using dynamic programming.
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?
Describe how you would optimize a slow-running SQL query.
Describe how you would optimize a slow-running SQL query.
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?
Stop tag and share joins from fanning out a page
resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.
Approach
- Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
- Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
- Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
- Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.
Follow-up
- The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
- A resource can be shared with the same user twice under different permissions. Does your count change, and should it?
What are the key differences between object-oriented and functional programming?
What are the key differences between object-oriented and functional programming?
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 the security of your applications?
How do you ensure the security of your applications?
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?
Explain the concept of RESTful APIs and their advantages.
Explain the concept of RESTful APIs and their advantages.
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?
Discuss the importance of version control in software development.
Discuss the importance of version control in software development.
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?
One log partition stops advancing while the others drain
Search results for a subset of tenants are hours stale; the rest are current. The projection consumer reports lag of zero on 15 of 16 partitions and 400,000 on one. Its error rate is flat and its CPU is idle. outbox_event has no pending rows older than a second, so the relay has published everything it holds. Identify the mechanism, give the ordered checks, and state what you do in the first ten minutes versus what you change permanently.
Approach
- Read the lag distribution first. A slow consumer lags everywhere; zero on fifteen partitions and 400,000 on one is not throughput. Idle CPU on the stuck partition means the consumer is not advancing its offset at all, which points at one message it cannot get past rather than at a rate problem.
- Exonerate the producer before touching the consumer. No pending outbox rows older than a second means the relay published, so the event exists in the log. This separates never sent from sent and never applied, which are different code paths and usually different owners.
- Read the message at the stuck offset and the handler's log lines for its event_id. A flat error rate with no progress has two explanations and you must distinguish them: the handler is throwing and the retry loop is swallowing it, or the handler is blocking on something and never returning. Idle CPU with no error lines favours the second.
- Mitigate before diagnosing further. Move the offending event to a dead-letter store and commit the offset past it. Adding consumers does nothing here, because a partition is consumed by exactly one member of the group, and the blast radius is every aggregate hashed to that partition, not only the aggregate that produced the bad event.
Follow-up
- The dead-lettered event carried aggregate_version 7 and the projection had applied 6. What must the replay do differently if 8 and 9 landed in the meantime?
- How do you show staleness to the user while the partition is behind, given the API already returns the projection's watermark?
Built from the rounds and topics Data Society candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Data Society loop
- Write out the reported sequence: Initial Screening, Technical Assessment, Behavioral Interview, Final Evaluation, Offer Discussion.
- 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 5 reported rounds, with the weakest marked.
02Work BI Reporting (Business Intelligence)
- Spend the session on BI Reporting (Business Intelligence), which Data Society candidates report being tested on.
- Write one worked example in BI Reporting (Business Intelligence) and time yourself on it.
Deliverable: One timed worked example in BI Reporting (Business Intelligence).
03Work Reporting Engineering
- Spend the session on Reporting Engineering, which Data Society candidates report being tested on.
- Write one worked example in Reporting Engineering and time yourself on it.
Deliverable: One timed worked example in Reporting Engineering.
04Work Data Analytics (Reporting & Insights)
- Spend the session on Data Analytics (Reporting & Insights), which Data Society candidates report being tested on.
- Write one worked example in Data Analytics (Reporting & Insights) and time yourself on it.
Deliverable: One timed worked example in Data Analytics (Reporting & Insights).
05Answer out loud: Technical / Domain Questions
- Answer aloud, timed: What are the key differences between object-oriented and functional programming?
- Answer aloud, timed: Describe how you would optimize a slow-running SQL query.
Deliverable: Spoken answers to 2 reported Technical / Domain Questions question(s), under time.
06Answer out loud: Coding / Algorithms
- Answer aloud, timed: Implement a function to find the longest substring without repeating characters.
- Answer aloud, timed: Write a function to reverse a linked list.
Deliverable: Spoken answers to 2 reported Coding / Algorithms question(s), under time.
07Answer out loud: Behavioral / Leadership
- Answer aloud, timed: Describe a challenging project you worked on and your role in it.
- Answer aloud, timed: How do you prioritize tasks when faced with multiple deadlines?
Deliverable: Spoken answers to 2 reported Behavioral / Leadership question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Describe a time you optimized a piece of code. What were the results?
Describe a time you optimized a piece of code. What were the results?
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 challenging project you worked on and your role in it.
Describe a challenging project you worked on and your role in 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?
How do you prioritize tasks when faced with multiple deadlines?
How do you prioritize tasks when faced with multiple deadlines?
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?
Provide an example of a time when you had to collaborate with a difficult team member.
Provide an example of a time when you had to collaborate with a difficult team member.
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?
What motivates you in your work?
What motivates you in your work?
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 failure or setbacks?
How do you handle failure or setbacks?
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?
- 01
Describe a time you optimized a piece of code. What were the results?
- 02
Describe a challenging project you worked on and your role in it.
- 03
How do you prioritize tasks when faced with multiple deadlines?
- 04
Provide an example of a time when you had to collaborate with a difficult team member.
What is the typical difficulty level of the interviews?
The interviews are medium to high in difficulty, focusing heavily on both technical skills and cultural fit. Expect to spend several weeks preparing, particularly for coding and system design challenges.
Data Society Software Engineer candidate reports ↗What differentiates successful candidates?
Successful candidates often demonstrate a combination of strong technical abilities, effective communication skills, and a clear alignment with Data Society's values.
Data Society Software Engineer candidate reports ↗What is the timeline from the initial screen to an offer?
Typically, the process can take 4–6 weeks, depending on scheduling and the number of interview rounds.
Data Society Software Engineer candidate reports ↗What is the company culture like at Data Society?
Data Society fosters a collaborative and innovative environment where employees are encouraged to share ideas and grow. The culture values data-driven decision-making and continuous improvement.
Data Society Software Engineer candidate reports ↗What topics does Data Society test in interviews?
Data Society interviews most often cover BI Reporting (Business Intelligence), Data Science (General), Reporting Engineering, Research Scientist role requirements, and Data Analytics (Reporting & Insights). The exact emphasis depends on the specific role you apply for.
Data Society Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Data Society Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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