Data QA Engineer

RudraTech It Solutions; India; À distance; INR 900 000 - 1 500 000; Plein temps

Avantages offerts par ce poste

100% remote flexibility

Core hours aligned to IST

Résumé du poste

RudraTech It Solutions is hiring a Data QA Engineer to design and run automated tests for batch and streaming data pipelines. You will validate ETL/ELT workflows across Snowflake, BigQuery, and other cloud warehouses, and implement quality rules to prevent data issues.

Collaborate with Data Engineers to set KPIs and integrate QA checks into CI/CD processes. You will work in a fully remote environment with IST core hours, contributing to auditable data pipelines for global clients in fintech,

Qualifications

• Must-have Python, SQL, PyTest, Great Expectations, Snowflake and BigQuery.
• Preferred Deequ, AWS Glue or Azure Data Factory, and Apache Airflow.
• Experience designing automated test suites for data pipelines.
• Experience validating ETL/ELT workflows across cloud warehouses.
• Knowledge of data quality rules and monitoring data drift.
• Familiarity with CI/CD integration using GitHub Actions or Jenkins.

Responsabilités

• Design and execute automated test suites for batch & streaming data pipelines using Python, SQL, and PyTest.
• Validate ETL/ELT workflows for accuracy, completeness, and timeliness across cloud warehouses (Snowflake, BigQuery, Redshift).
• Implement data quality rules (null checks, uniqueness, referential integrity) and monitor drift using Great Expectations or Deequ.
• Collaborate with Data Engineers to identify data gaps and define validation KPIs for pipeline health.
• Integrate QA checks into CI/CD workflows using GitHub Actions or Jenkins to block bad data releases.
• Document data quality standards, test cases, and failure root causes for cross-team transparency.

Connaissances

Python

SQL

PyTest

Great Expectations

Snowflake

BigQuery

CI/CD pipelines

Data validation frameworks

Outils

Deequ

AWS Glue

Azure Data Factory

Apache Airflow

Description du poste

About The Opportunity

A fast-scaling technology services firm operating in the Enterprise Data & AI quality assurance space, we build trusted, auditable data pipelines and validation frameworks for global clients across fintech, healthcare, and e-commerce. Our Data QA Engineers ensure data integrity, schema compliance, and pipeline reliability at scale—bridging engineering rigor with business logic to prevent downstream failures.

Role & Responsibilities

• Design and execute automated test suites for batch & streaming data pipelines using Python, SQL, and PyTest.
• Validate ETL/ELT workflows for accuracy, completeness, and timeliness across cloud warehouses (Snowflake, BigQuery, Redshift).
• Implement data quality rules (null checks, uniqueness, referential integrity) and monitor drift using Great Expectations or Deequ.
• Collaborate with Data Engineers to identify data gaps and define validation KPIs for pipeline health.
• Integrate QA checks into CI/CD workflows using GitHub Actions or Jenkins to block bad data releases.
• Document data quality standards, test cases, and failure root causes for cross-team transparency.

Skills & Qualifications

• Must-Have
• Python
• SQL
• PyTest
• Great Expectations
• Snowflake
• BigQuery
• CI/CD pipelines
• Data validation frameworks
• Preferred
• Deequ
• AWS Glue or Azure Data Factory
• Apache Airflow

Benefits & Culture Highlights

• 100% remote flexibility with core hours aligned to IST.
• Fast-track learning with exposure to multi-industry data ecosystems.
• Quarterly performance bonuses tied to QA automation impact metrics.

Skills: snowflake,python,sql