DataPilot

AI Mock Interview

A live, spoken interview with an AI interviewer — for any profession. Name the role you're applying for and add your resume, and it asks the questions most commonly asked for that job, generated fresh each session and calibrated to your level, style, and focus.

How it works:set the role you're interviewing for (and optionally your resume) above, and the interviewer asks the questions most common for that job — in any field. It speaks each question aloud and the mic starts listening automatically; answer out loud, then press “Done answering”. Expect follow-ups on shallow answers. Works best in Chrome or Edge; you can always type instead of speaking.

1 · Interview style

2 · Level & focus

3 · Interviewer voice

The interviewer introduces itself with the matching name and speaks with the closest voice your browser provides. Best voices (incl. English-India) are in Microsoft Edge; you can fine-tune the exact voice inside the session.

4 · Track

SQL Server DBA

Backups, Always On, Query Store, performance tuning, corruption recovery.

Questions generated fresh each session across 15 topic areas — e.g. backup, restore chains, and point-in-time recovery, Always On availability groups and failover, Query Store and plan regressions…

PostgreSQL DBA

MVCC, vacuum, replication, connection pooling, pg_stat_statements.

Questions generated fresh each session across 14 topic areas — e.g. MVCC internals, bloat, and vacuum tuning, EXPLAIN ANALYZE and the query planner, streaming and logical replication…

Cloud Database Engineer

RDS/Aurora, Azure SQL, migrations, HA/DR design, cost optimization.

Questions generated fresh each session across 12 topic areas — e.g. RDS vs Aurora architecture and trade-offs, Azure SQL Database vs Managed Instance, HA/DR design across regions and RPO/RTO…

Data Engineering

Pipelines, ETL/ELT, Azure SQL + ADF/Synapse/Fabric, Spark/Databricks, warehouse modeling.

Questions generated fresh each session across 15 topic areas — e.g. batch vs streaming architecture and when to use each, ETL vs ELT and modern data-stack design, Azure Data Factory / Synapse pipelines and orchestration…

Behavioral (STAR)

Incidents, conflict, prioritization, ownership — answered in STAR format.

Questions generated fresh each session across 9 topic areas — e.g. production incidents and outage ownership, disagreements and technical conflict, pushing back on risky changes or deadlines… · always STAR format