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TATA ELXSI Data Engineer Interview Questions

The questions to prepare for a TATA ELXSI Data Engineer interview. Questions from real interview reports rank first. Updated weekly.

30questions
~4htotal time
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1
CodingStart here. 4 questions · ~35 min
Merge Two Sorted ArraysEasy
Practice

Merge two sorted arrays into one sorted array using a two-pointer linear scan.

ArraysSortingTwo PointersTATA ELXSI
Top N Frequent ElementsHard

Tests algorithm design and efficiency for frequency-based retrieval problems.

Hash TablesArraysHeapTATA ELXSI
Time Complexity OptimizationHard

Tests algorithmic thinking focused on performance improvements for data retrieval.

Hash TablesArraysSearchingTATA ELXSI
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2
Pipelines24 questions · ~209 min
Real-Time Dashboard Pipeline DesignHard

Approach for building near-real-time dashboard pipelines with streaming, orchestration, and data quality controls.

Stream ProcessingSchedulingDependenciesTATA ELXSI
Warehouse Analytics ExperienceEasy

Discuss practical experience using a data warehouse for analytics, including loading, transformation, orchestration, and data quality.

InfrastructureData ModelingTATA ELXSI
Design Scalable Pipeline InfrastructureHard

Design the core pipeline infrastructure for a new project, with attention to orchestration, data quality, idempotency, and future scale.

InfrastructureToolsQualityTATA ELXSI
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3
More topics2 questions · ~17 min
Handling Anomalies in DataMedium

Tests your ability to diagnose data problems and apply SQL and data manipulation to fix them.

Data WranglingCase WhenAggregationsTATA ELXSI
SQL and NoSQL ExperienceEasy

Tests breadth of database experience relevant to building and operating UC San Francisco data systems.

JoinsData WranglingAggregationsTATA ELXSI
Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Monthly Sales Trends by CategoryMedium
Practice
Practice drill

Aggregate monthly sales by product category and use LAG to calculate month-over-month changes.

InfrastructureToolsData WranglingTotal Wine & MoreInc.Benjamin Moore
Contact Center Agent Performance MetricsHard
Practice
Practice drill

Compute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.

ETLAggregationsData ModelingADP
Handle Missing Financial Input ValuesMedium
Practice
Practice drill

Use joins, CTEs, and CASE logic to flag and fill missing financial fields for Qlik planning records.

Data WranglingETLQualityQlik
The finish line: interview-readyComplete all 30 questions plus 3 hands-on drills to finish this plan.