Junior Test Engineer

NTT DATA, Inc.; Indianapolis (IN); Sur place; USD 70 000 - 110 000; Plein temps

Résumé du poste

NTT DATA, Inc. in Indianapolis seeks a Software QA Analyst focused on data warehouse validation and migration testing. You will design and execute validation queries, compare source/target outputs across Snowflake, Databricks, and dbt, and log defects for root-cause analysis.

You will work with onshore/offshore teams, validate CDC/incremental loads, and perform regression tests across migration waves to ensure data integrity and accurate downstream reports.

Qualifications

• 2-4 years of experience in Software Testing / QA, with at least 2+ years in Data Warehouse / ETL testing.
• Practical experience in data migration / data platform modernization projects is strongly preferred.

Responsabilités

• Execute data validation queries to compare source vs target outputs.
• Perform row-count checks between source and target tables.
• Aggregate validations (sums, counts, averages, distinct counts, min/max).
• Sample and cell-level comparisons for critical entities and fields.
• Validate schema consistency (data types, lengths, precision/scale, nullable fields, constraints).
• Log discrepancies and support root-cause analysis with developers.

Connaissances

SQL

QA/testing

Data validation

Data migration

Cross-platform validation

Root-cause analysis

Outils

Snowflake

Databricks

dbt

Informatica

Description du poste

Job Duties: Roles & Responsibilities

• Execute data validation queries to compare:Source (Yellowbricks / Informatica outputs) vs Target (Databricks / Snowflake / dbt outputs).
• Perform:Row-count checks between source and target tables.
• Aggregate validations (sums, counts, averages, distinct counts, min/max).
• Sample and cell-level comparisons for critical entities and fields.
• Validate schema consistency (data types, lengths, precision/scale, nullable fields, constraints).
• Log discrepancies, analyze patterns, and work with developers to support root-cause analysis.
• Understand Informatica mappings and workflows and their expected outputs.
• Validate dbt models (staging, core, marts) on Snowflake against legacy Informatica outputs.
• Test Databricks notebooks/jobs that replicate Yellowbricks logic — ensuring correct transformations, joins, filters, and aggregations.
• Validate CDC / incremental loads: new, changed, and deleted records are handled correctly.
• Execute functional tests to verify correct application of business rules after migration.
• Perform regression testing for each migration wave to ensure that previously validated data and flows remain correct.
• Support integration testing across layers: Source → Databricks / Snowflakedbt → Snowflake → downstream reports or extracts.
• Validate downstream outputs (if in scope): reports, extracts, or interfaces that consume migrated data.
• Assist in executing basic performance tests for key queries and jobs (e.g., comparing runtime vs baseline).
• Monitor pipeline runs for job failures, retries, and data volume anomalies.
• Execute test cases, record results, and maintain traceability to requirements.
• Log defects with clear steps, data samples, and evidence (screenshots/SQL) in the defect tracking tool (e.g., JIRA, Azure DevOps).
• Retest resolved defects and support regression runs.
• Maintain test case repositories, test data sets, and execution logs for audit and re-use.
• Participate in daily stand-ups / defect triage with onshore/offshore teams.

Minimum Skills Required:

• Experience2-4 years of experience in Software Testing / QA, with at least 2+ years in Data Warehouse / ETL testing.
• Practical experience in data migration / data platform modernization projects is strongly preferred.

Technical Skills

• Strong SQL skills for writing complex queries and validations (joins, aggregations, window functions, filters).
• Hands-on experience testing on at least one data platform such as:Snowflake, Databricks, or other cloud DW/Big Data platforms – experience with Snowflake/Databricks is a plus.
• Exposure to Informatica (understanding mappings/workflows and expected outputs).
• Exposure to dbt or willingness to learn dbt-based validations (model outputs, dbt test results).
• Good understanding of data warehouse concepts: facts/dimensions, SCDs, aggregations, grain, source-to-target mapping.
• Familiarity with test management and defect tracking tools (e.g., Azure DevOps, JIRA, TestRail, qTest).
• Experience with Excel or similar tools for managing validation results and reconciliation artifacts.

Soft Skills

• Strong attention to detail and a structured approach to validation.
• Ability to analyze data discrepancies and collaborate with developers to narrow down issues.