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Dynatron Software • India
Role & seniority: QA Automation Engineer (senior level, 6–10+ years in data/analytics-focused QA)
Stack/tools: Data pipelines/ETL testing; Snowflake, Databricks, ADF, Airflow; SQL-based validation; Python automation; CI/CD, Git workflows; testing tools (Selenium, Postman, JMeter/Locust, Robot Framework, Great Expectations, dbt, Airflow, Fivetran)
Design, develop, and maintain automated test frameworks for data pipelines and ETL/ELT workflows; implement monitors for stream quality and CDC correctness
Create and execute detailed data test plans, validate data accuracy/integrity across ingestion to downstream layers; develop SQL validation scripts; perform root-cause analysis
Collaborate with Data Engineers/Analysts/Products; participate in agile ceremonies; drive QA best practices and produce reusable assets/frameworks
6–10+ years QA automation in data-intensive environments
Strong SQL, Python for automation; experience with ETL/ELT data workflows and cloud data platforms
Experience with Snowflake and at least one test automation framework; familiarity with CI/CD and Git
Databricks, ADF, AWS Glue, BigQuery, Redshift; streaming tech (Kafka/Kinesis/Debezium); metadata/lineage tools; dbt, Airflow, Fivetran
Experience with pytest/unittest/Behave; Selenium, API testing tools, performance testing tools; Great Expectations; Jira/XRay or similar
About Dynatron
Dynatron is transforming the automotive service industry with intelligent SaaS solutions that deliver measurable results for thousands of dealership service departments. Our proprietary analytics, automation capabilities, and AI-powered workflows empower service leaders to increase profitability, elevate customer satisfaction, and operate with greater efficiency. With accelerating demand and a rapidly expanding product ecosystem, we’re scaling fast, and we’re just getting started.
The Opportunity
We’re seeking a highly skilled and detail-oriented QA Automation Engineer to lead automated and manual testing efforts across our growing analytics and data engineering ecosystem. In this role, you’ll validate large-scale data workflows, strengthen data quality, and ensure the reliability of data moving across complex ETL/ELT pipelines. Your work will directly support the accuracy, consistency, and performance of mission-critical data systems used across Dynatron’s products and operations.
This position is ideal for an engineer with deep experience in data-centric QA automation, strong analytical thinking, and a passion for building scalable, reusable testing frameworks that guarantee our data is trustworthy, consistent, and ready for analytics and AI-driven innovation.
Important Information - Please Read
Because Dynatron does not have a physical office in India, this position will be structured as an Independent Contractor role.
No taxes will be deducted by Dynatron (contractor is responsible for compliance) No health insurance or employee benefits are provided India Gazetted Holidays and 24 days of PTO are included as part of the contract
Application & Interview Process
Submit an application through the company website, including a resume
Record a minimum 60-second introduction using Vocaroo (https: //vocaroo.com/) and paste the URL into the application
Participate in an online Screening Interview, scheduled between 8: 00 AM - 2:00 PM Eastern Time (USA) Participate in Round 1 Video Interview within the same time window Complete a technical assessment; successful candidates may be asked to discuss their solution in a follow-up interview
Participate in Round 2 Technical Interview, also between 8: 00 AM - 2:00 PM Eastern Time (USA)
Hours of Collaboration
6: 30 PM – 11:30 PM IST
9: 00 AM – 2:00 PM EST (USA)
8: 00 AM – 1:00 PM CST (USA)
7: 00 AM – 12:00 PM MST (USA)
6: 00 AM – 11:00 AM PST (USA)
An additional 3 flexible hours per day can be worked outside of core hours based on your preference.
What You’ll Do
Test Automation & Framework Development
Design, develop, and maintain automated test frameworks for data pipelines and ETL workflows Build reusable test components for Snowflake, Databricks, ADF, Airflow, streaming pipelines, and more Automate schema validation, regression testing, backfill testing, and data contract checks Implement automated monitors for stream quality, lag, CDC correctness, and consistency
Data Quality & Validation
Create, execute, and maintain detailed test cases, test plans, and regression suites for data enhancements Validate data accuracy, completeness, and integrity across ingestion, transformation, and downstream layers Develop SQL-based validation scripts to compare source vs. target datasets Perform root-cause analysis for data inconsistencies and work closely with engineering teams to resolve issues
Collaboration & Agile Delivery
Partner with Data Engineers, Analysts, and Product teams to understand transformation logic and business rules Participate in sprint ceremonies including requirement reviews, estimations, and deployment validations Monitor pipeline execution, identify defects early, and verify fixes through structured retesting
Quality Engineering Leadership
Drive QA best practices across multiple data environments Create documentation, reusable assets, and frameworks that elevate overall data quality discipline
What You Bring
6-10+ years of QA Automation experience in data-intensive or analytics-driven environments Strong proficiency in SQL for data validation, profiling, and regression testing Hands-on experience with Python for automation scripting and data validation Extensive experience testing ETL/ELT pipelines and cloud-based data workflows Deep understanding of QA methodologies, test planning, defect lifecycle management, and automation principles Experience with CI/CD pipelines, Git-based workflows, and automated execution environments Strong analytical and troubleshooting skills for identifying data quality issues Excellent written and verbal communication skills Hands-on experience with Snowflake and at least one test automation framework/tool
Preferred Qualifications
Experience with Databricks, ADF, AWS Glue, BigQuery, Redshift, or similar data platforms Exposure to streaming technologies such as Kafka, Kinesis, or Debezium Familiarity with metadata & lineage tools and dbt tests Experience with Airflow, dbt, Fivetran, or other orchestration platforms Experience with Python-based automation frameworks (pytest, unittest, Behave)
Work with a high-performance, globally distributed team shaping the future of data integrity and analytics quality Build automation frameworks that directly influence the reliability and speed of our data product ecosystem A remote-first environment with flexibility, autonomy, and strong cross-functional collaboration Opportunity to support a fast-scaling SaaS company redefining the under-innovated automotive service industry
If you thrive in data-driven environments, excel in automation, and want to make a measurable impact on product quality and engineering velocity, we’d love to meet you. Show more Show less