NTT Data

Global IT services and consulting provider.

Junior Test Engineer

Manual & Functional QAUpdated on Nov 14

Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

Two to four years of experience in software testing or quality assurance, including at least two years in data warehouse or ETL testing.
Strong SQL skills for complex queries and validations, including joins, aggregations, window functions, and filters.
Hands-on experience testing at least one data platform, such as Snowflake, Databricks, or another cloud data warehouse or big data platform.
Exposure to Informatica, including understanding mappings, workflows, and expected outputs.
Exposure to dbt or willingness to learn dbt-based validations, including model outputs and dbt test results.
Understanding of data warehouse concepts, including facts and dimensions, slowly changing dimensions, aggregations, grain, and source-to-target mapping.
Familiarity with test management and defect tracking tools such as Azure DevOps, JIRA, TestRail, or qTest.
Experience with Excel or similar tools for managing validation results and reconciliation artifacts.
Strong attention to detail and a structured approach to validation.
Ability to analyze data discrepancies and collaborate with developers to narrow down issues.

Responsibilities

Execute data validation queries comparing source Yellowbricks or Informatica outputs with target Databricks, Snowflake, or dbt outputs.
Perform row-count checks between source and target tables.
Perform aggregate validations, including sums, counts, averages, distinct counts, and minimum and maximum values.
Perform sample and cell-level comparisons for critical entities and fields.
Validate schema consistency, including data types, lengths, precision and scale, nullable fields, and 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 staging, core, and mart models on Snowflake against legacy Informatica outputs.
Test Databricks notebooks and jobs that replicate Yellowbricks logic, ensuring correct transformations, joins, filters, and aggregations.
Validate change data capture and incremental loads to confirm new, changed, and deleted records are handled correctly.
Execute functional tests to verify business rules after migration.
Perform regression testing for each migration wave to ensure previously validated data and flows remain correct.
Support integration testing across source-to-Databricks or Snowflake layers and dbt-to-Snowflake-to-downstream-report or extract layers.
Validate downstream reports, extracts, or interfaces that consume migrated data, when in scope.
Assist with basic performance tests for key queries and jobs, such as comparing runtime with baseline.
Monitor pipeline runs for job failures, retries, and data-volume anomalies.
Execute test cases, record results, and maintain traceability to requirements.
Log defects in the tracking tool with clear steps, data samples, and evidence such as screenshots or SQL.
Retest resolved defects and support regression runs.
Maintain test case repositories, test data sets, and execution logs for audit and reuse.
Participate in daily stand-ups and defect triage with onshore and offshore teams.

Desired Qualifications

Practical experience in data migration or data platform modernization projects is strongly preferred.
Experience with Snowflake or Databricks is a plus.

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 / Snowflake

dbt → 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: Experience

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.

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.

About the Company

NTT Data

Global IT services and consulting provider.

NTT DATA is a global IT and business services provider that helps organizations run and transform their technology and operations. It delivers consulting, industry solutions, cloud migration, cybersecurity, data analytics, and managed services to modernize systems and processes. It differentiates itself through its large scale, deep sector expertise in banking, healthcare, manufacturing, public sector, and automotive, and its broad ecosystem of partners with Microsoft, SAP, AWS, and Salesforce. Its goal is to help large enterprises digitally transform and optimize operations at scale using cloud-native approaches and secure IT environments.

Company size: 10,001+
Company stage: IPO
Headquarters: Tokyo, Japan
Founded: 1988

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