Top 20 Interview Questions & Answers for Data Technician (2025)

A Data Technician plays a critical role in ensuring data integrity, organization, and accessibility across systems. They work closely with data engineers and analysts to support the data infrastructure and quality pipelines. Below are categorized and up-to-date interview questions and answers to help you succeed in a 2025 Data Technician interview.

Behavioral Questions

• 1. Tell me about a time you had to clean a messy dataset.
  I handled missing values, corrected formats, and standardized column naming in a client database, improving report accuracy significantly.
• 2. Describe a situation where you found a critical data error.
  I spotted a duplicate entry issue in customer IDs during validation, corrected it, and improved the deduplication script for future prevention.
• 3. How have you collaborated with data analysts or engineers?
  I regularly work with analysts to understand their data requirements and with engineers to streamline ETL workflows and schema design.
• 4. Share a time you had to work under pressure to meet a data delivery deadline.
  I prioritized urgent fields, automated data validation, and batch processed files overnight to deliver before the next day's executive meeting.
• 5. What’s your approach when assigned a new unfamiliar data source?
  I start with data profiling to understand its structure, then document findings and clarify uncertainties with stakeholders.

Situational Questions

• 6. What would you do if a user reports inconsistent report results?
  I would trace back through the data pipeline, review logs and source tables, and verify the transformation steps for discrepancies.
• 7. How do you ensure timely data updates for business reports?
  I schedule automated ETL jobs, monitor job status daily, and use alerting systems to flag delays or failures immediately.
• 8. You find sensitive personal data in a public dataset—how do you handle it?
  I report the exposure immediately, restrict access, and follow data privacy protocols to remediate the issue securely.
• 9. How do you handle data integration from multiple systems?
  I match keys across datasets, resolve schema mismatches, and standardize formats before merging into the central data warehouse.
• 10. What steps do you take when an ETL job fails?
  I check logs, identify the error (e.g., nulls, source access issues), test a fix locally, and rerun the job after validation.

Technical Questions

• 11. What tools have you used for data extraction and transformation?
  I’ve worked with SQL, Python (pandas), Talend, and Excel macros to clean, extract, and transform data efficiently.
• 12. How do you validate data quality?
  I implement validation checks like null scans, range checks, duplicates, and referential integrity during ingestion or post-load.
• 13. What are some common causes of data inconsistency?
  Differences in data entry formats, source schema changes, manual updates, or sync failures often cause inconsistency.
• 14. Explain the difference between a primary key and a foreign key.
  A primary key uniquely identifies a record in a table, while a foreign key links records between two tables by referencing the primary key.
• 15. What’s your process for handling missing data?
  I assess the volume and impact, then use methods like imputation, removal, or default values depending on business and model context.

Cultural Fit Questions

• 16. How do you stay organized when working with large datasets?
  I maintain a clear folder structure, use naming conventions, and log every data transformation step for traceability.
• 17. How do you ensure transparency in your data work?
  I document each step in the process and share code, SQL scripts, and metadata so others can easily audit and replicate the work.
• 18. How do you keep up with trends in data management?
  I follow data blogs, attend webinars, and stay active in communities like DataOps and Reddit’s dataengineering subreddit.
• 19. Describe your ideal work environment as a Data Technician.
  I thrive in structured, process-oriented teams with clear documentation, collaboration tools, and regular communication channels.
• 20. Why do you want to work here as a Data Technician?
  I admire your data-first culture and believe my strong foundation in managing and maintaining reliable data pipelines fits your goals.