Bengaluru · Mid Level
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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.
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