Accenture in India Data Engineer Interview Questions
The questions to prepare for a Accenture in India Data Engineer interview. Questions from real interview reports rank first. Updated daily.
Design and implement SCD Type 1 and Type 2 dimensions with history tracking, idempotent loads, and data quality controls.
Approach for handling schema changes and data quality checks in a high-volume data lake pipeline.
Evaluates understanding of AWS orchestration and compute options for data engineering.
Evaluates capacity planning skills for running Spark workloads reliably on AWS.
Evaluates practical Spark performance tuning skills for production data pipelines.
Tests partitioning strategy knowledge and its impact on Spark performance and cost.
Tests prioritization under pressure across multiple projects, including time management, stakeholder communication, and ownership of trade-offs.
Explain OLTP vs OLAP designs, including schema shape, workload patterns, and when each is appropriate in a data platform.
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Design a tenant-isolated Mercury ledger schema and report posted account balances with transaction counts.
MercuryCreate Type 2 supplier lead-time history with effective dates, change detection, and current-record flags.
AndurilCompute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.
ADP