Senior Quality Engineer (QE) – Snowflake & Informatica Cloud

Experience: 7–10+ Years

Role: Senior Quality Engineer / Senior Data QA Engineer

Primary Skills: Snowflake, Informatica Cloud (IICS/IDMC), SQL, ETL/ELT Testing, Data Validation

Role Overview

We are looking for an experienced Senior Quality Engineer (QE) with strong expertise in testing modern data platforms built on Snowflake and Informatica Cloud (IICS/IDMC).

The candidate will be responsible for end-to-end validation of data ingestion, transformation, integration, and data warehouse processes, ensuring data accuracy, completeness, consistency, and reliability across source and target systems.

The ideal candidate should possess strong SQL skills, hands-on experience with Informatica Cloud pipelines, and the ability to independently develop and execute comprehensive data testing strategies.

Key Responsibilities

Develop and execute test strategies, test plans, test scenarios, and test cases for data engineering and data warehouse solutions.

Perform end-to-end testing of Informatica Cloud (IICS/IDMC) data integration pipelines with Snowflake as the target/data platform.

Perform source-to-target data validation across source, staging, transformation, and target layers.

Validate

Record counts and data completeness

Field-level data accuracy

Data types and formats

Transformation and business rules

Null and duplicate handling

Referential integrity

Data reconciliation and aggregation

Write complex SQL queries in Snowflake for data validation, reconciliation, and defect investigation.

Validate IICS/IDMC mappings, mapping tasks, taskflows, transformations, schedules, dependencies, and error-handling processes.

Perform testing of full loads, incremental loads, CDC processes, historical loads, and SCD Type 1/Type 2 implementations.

Validate restart, recovery, failure-handling, and reprocessing scenarios for data pipelines.

Test Snowflake objects including tables, views, stages, streams, tasks, stored procedures, and transformations, as applicable.

Perform functional, integration, regression, system, data quality, and performance testing of data pipelines.





Validate data across heterogeneous sources including databases, files, APIs, and cloud-based applications.

Perform root-cause analysis of data discrepancies and collaborate with Data Engineers to resolve defects.

Validate production fixes, enhancements, and data pipeline changes through regression testing.

Identify opportunities to automate repetitive data validation and regression testing.

Track defects and provide clear reporting on test execution, defects, quality risks, and release readiness.

Participate in requirements, design, source-to-target mapping, and technical reviews to identify potential quality issues early.

Mentor junior QE resources and contribute to establishing data testing standards and best practices.

Mandatory Technical Skills

7–10+ years of overall experience with strong experience in ETL/ELT, Data Warehouse, and Data Engineering testing.

Strong hands-on experience with Snowflake.

Strong hands-on experience with Informatica Cloud – IICS/IDMC, particularly Cloud Data Integration.

Advanced SQL skills, including:

Complex joins

CTEs

Subqueries

Aggregations

Window/analytical functions

Data reconciliation queries

Strong understanding of ETL/ELT architecture and data integration concepts.

Experience with source-to-target validation and large-volume data reconciliation.

Strong understanding of data warehousing and dimensional modeling concepts.

Experience testing SCD Type 1/Type 2, CDC, incremental/delta loads, and historical data loads.

Experience validating data quality dimensions including accuracy, completeness, consistency, uniqueness, validity, and timeliness.

Experience with defect/test management tools such as JIRA or Azure DevOps.

Good understanding of Agile/Scrum delivery methodologies.





Test Automation Skills – Preferred

Experience automating data validation using Python, PyTest, SQL-based automation frameworks, or similar technologies.

Ability to develop reusable utilities for:

Source-to-target comparison

Record-count reconciliation

Field-level comparison

Data quality checks

Regression testing

Exposure to data quality/testing frameworks such as Great Expectations, Soda, dbt tests, or similar tools.

Understanding of integrating automated data tests into CI/CD pipelines.

Good to Have

Experience with Informatica Cloud Data Quality (CDQ).

Knowledge of other IDMC capabilities such as Cloud Data Integration (CDI), Cloud Application Integration (CAI), and Mass Ingestion.

Experience working with cloud platforms such as Azure or AWS.

Experience testing REST APIs and file formats such as CSV, JSON, XML, and Parquet.

Understanding of Snowflake security concepts, roles, access controls, and data masking.

Exposure to data governance, metadata management, and data lineage.

Experience working on enterprise data migration or cloud data modernization programs.

Behavioral Expectations

Robust analytical and troubleshooting capabilities for identifying complex data issues.

Ability to independently own end-to-end QE activities for a data workstream.

Strong attention to detail and focus on business-critical data scenarios.

Ability to identify testing gaps and quality risks proactively rather than relying only on predefined test cases.

Strong communication and stakeholder-management skills.

Ability to collaborate effectively with Data Engineers, Architects, Business Analysts, Product Owners, and business stakeholders.

Ability to mentor junior QE resources and drive testing best practices within the team.

Key Skills

Snowflake | Informatica Cloud (IICS/IDMC) | Cloud Data Integration (CDI) | ETL/ELT Testing | Data Warehouse Testing | Advanced SQL | Source-to-Target Testing | Data Reconciliation | Data Quality Testing | SCD/CDC Testing | Regression Testing | Python Automation | Agile | JIRA/Azure DevOps

📌 SENIOR QUALITY ENGINEER | SNOWFLAKE + INFORMATICA CLOUD (Bengaluru)
🏢 Brihati Global Edge Solutions
📍 Bengaluru