Amdocs ETL Testing Interview Questions

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What Is ETL Testing? (Definition + Amdocs Telecom Example)

ETL Testing is the process of validating data during Extract, Transform, and Load operations to ensure accuracy, completeness, consistency, auditability, and performance in a Data Warehouse (DW).

Amdocs real-world context

In telecom and billing platforms delivered by Amdocs, ETL testing plays a critical role in:

  • Usage data processing (CDRs – Call Detail Records)
  • Billing, invoicing, and revenue assurance
  • Customer analytics, churn, and regulatory reporting

An ETL tester at Amdocs must ensure that millions of usage records, complex tariff calculations, and aggregations are processed accurately and on time, making interviews highly scenario-based and SQL-focused.

Data Warehouse Flow: Source → Staging → Transform → Load → Reporting

  1. Source – BSS/OSS systems, CRM, billing engines, flat files
  2. Staging – Raw data landing (no business rules)
  3. Transformation – Tariff logic, joins, aggregations, SCD handling
  4. Load – Fact and Dimension tables
  5. Reporting – Billing reports, revenue dashboards, analytics

Amdocs ETL Testing Interview Questions & Answers

(Basic → Advanced | Telecom & Real-Time Focus)

🔹 Basic ETL Testing Questions (1–15)

  1. What is ETL testing?
     Validation of data accuracy and transformations during ETL processing.
  2. Why is ETL testing important at Amdocs?
     Because telecom billing and usage data directly impact customer invoices and revenue.
  3. What is Source-to-Target (S2T) mapping?
     A document defining source fields, transformation logic, and target columns.
  4. What are the types of ETL testing?
     Source testing, staging testing, transformation testing, target testing, reconciliation, performance testing.
  5. What is staging area testing?
     Ensuring staging data exactly matches source data.
  6. What are audit fields?
     load_date, batch_id, created_by, updated_date.
  7. How do you validate record counts?
     Compare source vs target counts after transformations.
  8. What is data reconciliation?
     Matching totals and counts between source and target.
  9. Difference between fact and dimension tables?
     Facts store measures (usage, charges); dimensions store descriptive data (customer, plan).
  10. What is full load vs incremental load?
     Full load reloads all data; incremental load processes deltas only.
  11. What is reject data testing?
     Validating records rejected due to data quality or rule violations.
  12. What is mapping validation?
     Verifying ETL logic strictly follows S2T mapping.
  13. What is end-to-end ETL testing?
     Source → DW → Report validation.
  14. Why is SQL mandatory for ETL testers?
     SQL validates joins, aggregations, and transformations.
  15. What is data quality testing?
     Checking accuracy, completeness, and consistency.

🔹 Scenario-Based Intermediate Questions (16–35)

  1. Scenario: Source has 10 million CDRs, target has 9.8 million. What do you check?
     Reject records, filters, duplicate elimination, join conditions.
  2. How do you test NULL handling?
     Validate mandatory columns and default value logic.
  3. What is SCD Type 1?
     Overwrites old values without maintaining history.
  4. What is SCD Type 2?
     Maintains history using effective_from, effective_to, and current_flag.
  5. Scenario: Customer plan changes. What do you test?
     SCD2 history creation for customer-plan dimension.
  6. What is surrogate key testing?
     Ensure surrogate keys are unique and non-null.
  7. What is late-arriving dimension?
     Usage fact arrives before customer or plan dimension.
  8. Scenario: Duplicate usage records appear in target. Why?
     Incorrect joins or missing deduplication logic.
  9. How do you test aggregation logic?
     Compare aggregated usage or charges with source totals.
  10. What is hashing used for?
     Change detection and deduplication.
  11. How do you test CDC (Change Data Capture)?
     Validate only changed or new records are loaded.
  12. Scenario: Negative charge appears in billing report. What do you test?
     Tariff and discount transformation logic.
  13. What is referential integrity testing?
     Fact foreign keys must exist in dimension tables.
  14. Scenario: Data type mismatch during load. What to validate?
     Precision, scale, and truncation rules.
  15. How do you test date transformations?
     Time zone and billing-cycle validation.
  16. What is soft delete testing?
     Validate logical delete flags instead of physical deletion.
  17. Scenario: ETL job rerun creates duplicates. Why?
     Restartability logic failure.
  18. What is schema drift?
     Source schema changes impacting ETL.
  19. How do you validate billing reports?
     Reconcile report totals with DW tables.
  20. What is data masking testing?
     Ensuring PII (MSISDN, customer info) is masked.

🔹 Advanced & Real-Time Amdocs Scenarios (36–55)

  1. Scenario: ETL job misses SLA during peak billing. What do you analyze?
     Query plans, indexing, partitioning, parallelism.
  2. How do you test ETL performance tuning?
     Validate join strategy and execution plans.
  3. Scenario: Many-to-many join inflates usage data. What test?
     Join cardinality validation.
  4. How do you validate window functions?
     Check ranking, deduplication, and SCD logic.
  5. Scenario: Late usage data impacts monthly bill. What do you do?
     Recalculate impacted billing periods.
  6. How do you test audit/control tables?
     Validate batch status, row counts, and load times.
  7. Scenario: Billing report mismatch with DW. First step?
     Verify S2T mapping and aggregation grain.
  8. How do you test ETL rollback?
     Ensure partial loads are reverted safely.
  9. Scenario: Parallel jobs cause deadlocks. What test?
     Concurrency and locking validation.
  10. How do you test historical reloads?
     Check duplication and SCD handling.
  11. Scenario: Source file arrives late. What to test?
     Dependency and rerun logic.
  12. How do you validate checksum/hash totals?
     Compare source vs target hashes.
  13. Scenario: Currency conversion mismatch for roaming charges. What to validate?
     Exchange rate tables and logic.
  14. How do you test cloud ETL pipelines?
     Scalability, cost, and performance.
  15. Scenario: NULLs after LEFT JOIN. Why?
     Missing dimension records.
  16. How do you test archival logic?
     Validate movement to history tables.
  17. Scenario: Incorrect SCD expiry date. Root cause?
     Effective date logic issue.
  18. How do you validate metadata tables?
     Batch IDs, timestamps, and counts.
  19. Scenario: Sudden spike in usage data. What test?
     Source anomaly and business rule validation.
  20. How do you perform end-to-end ETL testing at Amdocs?
     Source → DW → Billing/Analytics reconciliation.

Real SQL Query Examples for ETL Validation

Sample Tables

  • src_usage(call_id, msisdn, duration, charge, call_dt)
  • dim_customer(cust_sk, msisdn, current_flag)
  • fact_usage(call_id, cust_sk, charge, load_dt)

1️⃣ Record Count Validation

SELECT COUNT(*) FROM src_usage;

SELECT COUNT(*) FROM fact_usage;

2️⃣ JOIN Validation

SELECT COUNT(*) AS missing_dim

FROM fact_usage f

LEFT JOIN dim_customer d

ON f.cust_sk = d.cust_sk

WHERE d.cust_sk IS NULL;

3️⃣ GROUP BY Aggregation

SELECT msisdn, SUM(charge)

FROM src_usage

GROUP BY msisdn;

4️⃣ Window Function – Deduplication

SELECT *

FROM (

  SELECT call_id,

         ROW_NUMBER() OVER (PARTITION BY call_id ORDER BY call_dt DESC) rn

  FROM src_usage

) t

WHERE rn = 1;

5️⃣ Performance Tuning Validation

EXPLAIN

SELECT *

FROM fact_usage

WHERE load_dt >= CURRENT_DATE – 1;

ETL Tools Commonly Asked in Amdocs Interviews

  • Informatica
  • Microsoft SQL Server Integration Services
  • Ab Initio
  • Pentaho
  • Talend

ETL Defect Examples + Test Case Sample

Defect Example

Issue: Duplicate usage records in billing fact table

  • Root Cause: Incorrect join and missing dedup logic
  • Fix: Correct join keys and apply window-function-based deduplication

Sample Test Case

  • Test Case: Validate SCD2 customer plan change
  • Expected Result:
    • Old plan record expired
    • New plan record inserted with current_flag = ‘Y’

Amdocs ETL Testing – Quick Revision Sheet

  • Validate record counts, sums, NULLs, duplicates
  • Check S2T mappings line-by-line
  • Test SCD1, SCD2, audit fields, hashing
  • Use JOIN, GROUP BY, window functions
  • Always reconcile source vs target vs billing reports

FAQs (SEO & Snippet Friendly)

Q1. What are Amdocs ETL testing interview questions?
 They focus on telecom usage, billing accuracy, and real-time ETL scenarios.

Q2. Which SQL is important for Amdocs ETL roles?
 JOINs, GROUP BY, window functions, and performance tuning queries.

Q3. How do you test SCD2 in telecom projects?
 By validating history rows, effective dates, and current flags.

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